From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven.

About the Role

Fivetran + dbt Labs is building data pipelines to power the modern data stack for thousands of companies.

We're looking for a Lead Company Operations Manager to join the COO Office — the team responsible for setting the pulse of the company: developing our strategies, holding leaders accountable for executing them, and taking on the cross-functional work that lacks a clear owner.

This role owns Leadership Operations: the standing forums and rhythm through which NewCo's leadership runs the business. You will own the mechanics behind our board meetings, help run the ELT's operating rhythm and quarterly Strategy Days, and make sure the decisions made in those forums are carried through to closure. Your remit is what happens in the room — forum design, agendas, pre-reads, decision capture, and follow-through — and the calendar of forums, planning cycles, and decision points that connects them.

The work is deliberately diverse. One week you're building the narrative and data behind a board deck with the executive leadership team; the next you're redesigning a cadence that is consuming more executive time than it returns, or scoping a special project that arrived without a brief, an owner, or a definition of done. You'll work directly with stakeholders at every level across Product, GTM, Finance, and Engineering — from individual contributors who own the underlying work to the executives accountable for it — and you'll be expected to bring structure to problems that show up without any.

You'll join a small, central team in the middle of the Fivetran + dbt Labs integration, so expect to build mechanisms that don't exist yet rather than inherit mature ones. Early on, your impact will come mostly from the structure, materials, and follow-through behind our leadership forums, with a clear path to owning more of the live facilitation as you build relationships with the executive team.

This is a full-time position based out of our Oakland office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team.

This position reports to the Director of Business Operations & Chief of Staff to the COO.

What You'll Do

Executive Rhythm of the Business

Own and maintain the integrated calendar of executive forums, planning cycles, and decision points.
Improve the rhythm itself: identify cadences that are duplicative, low-signal, or consuming more executive time than they return, and propose changes.
Make sure each forum has a clear purpose, owner, input set, and decision output — and that they don't collide or duplicate each other.

Board Meetings

Own end-to-end preparation of board materials: build the storyline, partner with Finance and department leaders on the underlying data, and manage review cycles with the ELT.
Maintain a reliable source of truth for board and executive reporting metrics so numbers reconcile across Finance, GTM, and Product reporting.
Synthesize scattered executive inputs into a single, decision-ready artifact — a doc, model, or deck that moves the conversation forward.
Partner with the COO's Executive Assistant, who owns scheduling and logistics, so content and logistics stay in lockstep.

ELT Strategy Days

Help run the quarterly ELT Strategy Days: topic selection, agendas, pre-reads, facilitation materials, and clean capture of every decision with a named owner and date.
Shape Strategy Days around the priorities most likely to propel the business forward rather than a standing agenda.
Carry decisions and action items out of each session, drive them to completion with the accountable ELT member and their department operations team, and bring unresolved items into the next session.

Weekly ELT Meetings

Help run the weekly ELT meeting: topic selection, agendas, pre-reads, facilitation materials, and clean capture of every decision with a named owner and date.
Close the loop between the weekly meeting and Strategy Days. Track decisions and action items across both, drive them to completion with the accountable ELT member and their department operations team, and bring status and open items back into the next session.
Remove blockers rather than just report status, escalate early when something is stuck, and be able to show what measurably changed as a result of these cadences.

SLT Engagements

Lead and facilitate recurring engagement with the SLT — VPs and above — to leverage their perspective and influence, and keep them abreast of happenings across the business.

Strategic Initiatives and cross-functional support

Take on ambiguous, cross-functional initiatives assigned to the COO Office, from initial framing through delivery. Roughly 20% of your capacity is reserved for this unplanned work.
Structure new work quickly with a clear charter: problem statement, success measures, decision rights, stakeholders, and timeline.
Drive projects to measurable outcomes without formal authority, influencing peers and executives across functions.
Transition completed initiatives to a permanent owner with the documentation and mechanisms needed to sustain them.

Skills We're Looking For

Proven experience (5+ years) in program management, business operations, strategy, or chief of staff roles, supporting stakeholders at all levels, up to and including senior executives.
Demonstrated ownership of executive or board-level forums: you've designed agendas, produced pre-reads, captured decisions, and made follow-through stick.
Credible in the room with senior leaders, with the appetite to grow into leading executive forums yourself. Much of the face-to-face facilitation is driven by the Chief of Staff today; you'll build toward taking more of it on.
Systems thinker — you look for the underlying mechanism, not the one-off fix, and you design processes others can run without you.
Owner mentality with a high tolerance for ambiguity; you take unclear requests, define the problem, and drive to a positive outcome without waiting to be told how.
Exceptional written and verbal communication, with a track record of tailoring the same message for an individual contributor, a department leader, and a board audience.
Comfortable with data — able to work in spreadsheets, run ad hoc analysis, pressure-test numbers from other teams, and translate results into a clear recommendation.
Experience with program management tools and methodologies, and a demonstrated ability to run multiple concurrent work streams without losing detail.

Required AI competencies

Use conversational AI systems (like Claude, ChatGPT, and internal chatbots) to research, author, review, and synthesize operational artifacts such as board narratives, process documents, and executive updates.
Build repeatable AI workflows — prompts, skills, or agents — rather than treating AI as a one-off drafting tool.
Evaluate AI output critically, including knowing when the task calls for human judgment instead.

Bonus Skills

Experience preparing board materials at a private, VC- or PE-backed company.
Experience supporting post-merger integration or another period of significant organizational change.
Experience standing up or rationalizing an executive operating cadence from scratch.
Familiarity with BI tooling (Looker) and basic SQL.
Light scripting or low-code automation experience for building internal tools.
Prior experience in B2B SaaS, with working fluency in ARR, NRR, pipeline, and margin.

#LI-Hybrid #LI-SR1

The compensation range displayed on this job posting reflects the minimum and maximum target for new hire compensation for the target position and level, and may include sales incentives or target bonuses depending on the role. Our compensation ranges are determined by role, level, and location. Our job titles may span more than one career level. Within the range, individual compensation is determined by additional factors, including job-related skills, experience, relevant education or training, business need, market demands. The compensation range is subject to change and may be modified in the future. Your recruiter can share more about the specific compensation range for your location during the hiring process.

Oakland Pay Range

$179,667—$224,583.50 USD

Perks and Benefits

100% employer-paid medical insurance*
Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off.
RSU stock grants*
Professional development and training opportunities
Company virtual happy hours, free food, and fun team-building activities
Monthly cell phone stipend
Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents.

*May vary by country and worker type - please reach out to your recruiter for more information

Click here to learn more about Fivetran's Benefits by Region.

We’re honored to be valued at over $5.6 billion, but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream. Read about us in Forbes.

Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities.

To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video.

To learn more about our candidate privacy policy, you can read our statement here.

We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form. We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

Oakland Pay Range 179667 - 224583.5 USD

About the company

Fivetran moves data from business applications and databases into cloud analytics systems so data teams can work with reliable records instead of building pipelines by hand. Its ready-made connectors handle changes in source tables and software interfaces, reducing the maintenance needed to keep information up to date. Teams also use its transformation tools to turn raw records into datasets for reporting, operations and AI applications. Fivetran charges for usage, measuring the distinct records changed each month and the data models run, with plans for different security and operational needs. Founded in 2012, Fivetran is headquartered in Oakland, California.

Company Size

1,001-5,000

Company Stage

Debt Financing

Total Funding

$852.7M

Headquarters

Oakland, California

Founded

2012

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Simplify's Take

What believers are saying

Its product scope widened: the June 2026 dbt Labs merger joins data movement with transformation and governed business definitions.
Customers buy measurable time savings: Okta reports nearly 1,000 hours saved annually with Fivetran.
New hires receive equity grants: Fivetran advertises stock grants for all new hires and annual refresh grants.

What critics are saying

Customer usage adds up: Fivetran counts identical source records separately when connections feed multiple destinations.
Delivery has limits: Fivetran delays syncs at source request quotas and reloads tables lacking support for incremental updates.
Plan for office attendance: Fivetran's published hybrid model calls for two office days each week.

What makes Fivetran unique

Sensitive data stays local: Fivetran's managed Hybrid Deployment runs pipelines inside customers' own networks.
Open storage reduces lock-in: Fivetran maintains Iceberg and Delta tables that multiple computing engines read.
Data flows both directions: Fivetran Activations sends warehouse audiences into advertising and sales tools.

Help us improve and share your feedback! Did you find this helpful?

Benefits

Health Insurance

Unlimited Paid Time Off

Stock Options

Professional Development Budget

Phone/Internet Stipend

Mental Health Support

Growth & Insights and Company News

Headcount

6 month growth

1 year growth

2 year growth

Cyparta

Sep 16th, 2026

dbt v2 goes GA: what the Rust rewrite and dbt State mean for your data team.

dbt v2 goes GA: what the Rust rewrite and dbt State mean for your data team. At dbt Summit 2026 on September 16, Fivetran + dbt Labs made dbt v2, a full Rust rewrite, generally available alongside dbt State and a wave of agent-focused previews. By eslam elhadedy

dbt Labs

Sep 16th, 2026

Fivetran + dbt Labs announces new capabilities to make enterprise data agent-ready at dbt summit 2026.

Fivetran + dbt Labs announces new capabilities to make enterprise data agent-ready at dbt summit 2026. Last edited on Sep 16, 2026 Fivetran + dbt Labs makes dbt v2 and dbt State generally available, alongside the debut of Fivetran Context Layer, dbt Charts and a new open lakehouse vision for greater flexibility across storage and compute LAS VEGAS - September 16, 2026 - Fivetran + dbt Labs today announced the general availability of dbt v2 and dbt State, delivering new levels of speed and cost optimization, and introduced Fivetran Context Layer, new dbt Wizard experiences, dbt Charts and an open lakehouse vision for greater flexibility across storage and compute. As enterprises deploy AI agents into production, they need trusted data, context the business controls, and the flexibility to work across the platforms, models and tools already in use. To meet these demands, Fivetran + dbt Labs is advancing its vision for Open Data Infrastructure: a vendor-neutral, interoperable architecture that lets organizations independently choose and evolve their storage, compute, data movement, transformation and visualization technologies at every layer. This enables AI systems to work across platforms using data and context the enterprise owns, not a single vendor. "Every model our customers have built, every test they've written, every metric they've defined already captures the context AI agents need to do meaningful work," said Anjan Kundavaram, Chief Product Officer, Fivetran + dbt Labs. "What we're delivering now is the open infrastructure to put that context to work across systems, while giving organizations the freedom to choose how their data is stored, moved, transformed and used as AI evolves." A faster, more efficient engine with deeper SQL understanding dbt v2 is a full Rust rewrite of the dbt engine built for the scale that teams run at today and for how agents write SQL. It parses a 10,000-model project up to 10x faster than v1 and gives teams and their agents accurate real-time feedback, surfacing errors, column checks, and lineage before anything runs. With this release, the two engine era of Core and Fusion ends. Now, dbt is one engine with two versions: dbt Core v1, the python implementation, is dbt v1. Fusion, the Rust implementation, has become dbt v2. Both versions remain Apache 2.0-licensed and security-supported. dbt State determines what has changed by checking warehouse metadata and model SQL, then builds, skips, clones or defers each run accordingly. This simplifies orchestration and allows engineers to iterate faster without complex development rituals, while reducing unnecessary warehouse compute. "dbt State has been a paradigm shift for how we work," said Gordon Curzon, Head of Analytics Engineering, Virgin Media O2. "With freshness codified, simpler orchestration, and freed-up developer capacity, we focus more time on initiatives that add value to our business on top of the 25% savings on both job run time and BigQuery compute costs." More flexibility across storage and compute Open Data Infrastructure centers on a customer-owned data layer built on open formats, avoiding vendor lock-in for storage and compute so organizations can store data once and access it through different engines for different use cases. Fivetran's Managed Data Lake Service, already generally available, organizes, structures and maintains data as managed Apache Iceberg(TM) tables in customers' own cloud storage. Lake Compute, now in Private Beta, is a single-node SQL engine built on DuckDB and runs dbt models directly against Apache Iceberg(TM) tables, built and priced specifically for transformation, not general-purpose compute. Together, the two give teams the flexibility to run each workload on whichever engine fits best, optimizing cost without re-platforming. An open standard for agent context Agents are only as trustworthy as the context they can access. Fivetran Context Layer (Private Beta) unifies the data and metadata needed to give LLMs and AI agents relevant context, building on dbt's structured context and adding unstructured knowledge, like docs and Slack threads. This service uses Agents Schema, an open source standard, that centralizes context in a structured, extensible format directly in the data warehouse. The context is accessible to teams via preferred MCP or AI tools, including generally available integrations through AI marketplaces including Anthropic and a plugin in ChatGPT. One agent, grounded in your dbt project - wherever you work Coding agents can now write SQL as well as most engineers, but writing code isn't the same as understanding a governed dbt project, including its lineage, its tests, its contracts, and what breaks when something changes. dbt Wizard in the dbt platform (Public Preview) is built to close that gap. It's natively connected to your project, knows which tool to call, pulls the right context automatically, and proactively validates changes before they ship. Wizard is also expanding beyond the dbt platform with Wizard CLI (Public Beta), bringing the project-grounded agent directly into the terminal, and Wizard Desktop (Private Beta), a dedicated local workspace for longer, more complex work. Wizard Explore Mode (Public Preview) brings conversational analytics to business users, enabling them to ask questions in plain language and get answers grounded in the same dbt project the data team maintains. When an answer falls short, those questions can also surface what the data team should improve next. A shared language for BI, built for humans and agents dbt Charts (Public Beta) brings governed BI alongside the models it depends on. Instead of governance living in a separate, closed tool, they are defined as YAML and version-controlled alongside the dbt models they reference, creating a shared, declarative format that both humans and AI agents can read, write and review. Customers building with Fivetran + dbt Labs "Since rolling out dbt State, we've reduced warehouse costs by 59% on scheduled jobs in dbt platform," said Chris Shepherd, Principal Data Engineer, RxBenefits. "That's $8,173.23 in the first 60 days alone on top of a Snowflake adaptive warehouse. We've reused 716k models instead of rebuilding, which reduced query run time a total of 14 days, 11 hours, and 15 minutes over the same period." "We've been impressed by the flexibility Lake Compute gives us. Now we can choose where each dbt workload runs, and use whichever engine actually fits the job," said Tyson Doberneck, Senior Data Engineer, Obie. "dbt Wizard is changing how we work. Instead of hand-coding everything, we draft logic with an agent that already has full context on our jobs and our codebase. No more finding and uploading a manifest file just to explain myself, that step used to slow down every request. Now we're pointing it at sales and marketing data too, so analysts get answers themselves instead of waiting on my team," said Farin Fukunaga, Data Engineering Lead, Paylocity. About Fivetran + dbt Labs Fivetran + dbt Labs deliver the data infrastructure layer that makes agents trustworthy - from the moment data moves, through every transformation, to the context an agent reasons from. The Fivetran platform moves, manages, and transforms data from every system a business runs on into a secure, reliable foundation engineered to evolve, with the flexibility to work across clouds, engines, and tools. With Fivetran, analytics, operations, and AI run on data you trust and control. Thousands of organizations worldwide, including OpenAI, LVMH, Pfizer, and Verizon, rely on Fivetran to turn data into a competitive advantage. Learn more at Fivetran.com, or follow Fivetran on LinkedIn. Since 2016, dbt Labs has been on a mission to help data practitioners create and disseminate organizational knowledge. dbt is the standard for AI-ready structured data. Globally, more than 100,000 data teams use dbt, including those at Siemens, Roche and Condé Nast. Learn more at getdbt.com, and follow dbt Labs on LinkedIn, X, Instagram, and YouTube.

MarTech360

Sep 11th, 2026

Fivetran promotes Natasha Lockwood to Lead of Product-Led Growth Marketing.

Fivetran promotes Natasha Lockwood to Lead of Product-Led Growth Marketing. Fivetran has promoted Natasha Lockwood to Lead of Product-Led Growth Marketing, expanding her responsibilities within the company's marketing organization. Lockwood's role focuses on product-led growth (PLG), an approach that connects product experiences with customer acquisition, engagement, and expansion. Her appointment comes as B2B software companies continue to explore ways to make the product itself a larger part of the marketing and customer journey. At Fivetran, Lockwood has built experience in digital strategy and cross-channel marketing. Her professional profile describes her focus as PLG marketing within B2B SaaS, alongside expertise in digital strategy and cross-channel campaigns. The expanded role places product-led growth more directly within Fivetran's marketing efforts. For B2B technology companies, PLG can involve using product usage signals, customer behaviour, digital experiences, and targeted campaigns to create more connected paths from initial interest to adoption. The shift is also part of a broader change in B2B marketing, where traditional lead-generation models are increasingly being complemented by product experiences. Rather than relying only on sales outreach or content to move prospects through the funnel, PLG strategies can use how customers interact with a product to inform marketing and engagement. For marketers, this creates a closer relationship between marketing, product, data, and customer experience teams. It also places greater importance on understanding user behaviour and identifying opportunities to support adoption throughout the customer lifecycle. Lockwood's promotion reflects that evolving role of marketing within SaaS businesses, where product engagement and customer behaviour are becoming increasingly important inputs for growth strategies. Her new position at Fivetran will focus specifically on product-led growth marketing as the company continues to develop its approach to reaching and engaging B2B technology buyers.

Slalom

Aug 17th, 2026

4 trends for activating data with context.

4 trends for activating data with context. Takeaways from Slalom's Insurance Leaders Lunch at the Databricks Data & AI Summit. Matt Edwards Senior Director Published: Aug 17, 2026 Tl;dr. * Slalom, in partnership with Atlan, Fivetran and Databricks, hosted an Insurance Leaders Lunch and panel discussion during the 2026 Databricks Data & AI Summit. Insurance, data, and AI leaders discussed, How do insurers move from having data to activating it to driving smarter decision-making? * The session opened by framing the challenges around four interconnected trends reshaping the industry. Those trends are human-AI collaboration, data fluidity and intelligent systems, ecosystem modularization, and self-directed systems. * The throughline connecting all four trends? Context. Context = shared definitions, data lineage, quality, regulatory constraints, and the "why" behind a recommendation. - Without context, even the most sophisticated AI systems fall flat in insurance operations. Thank you to its community of panelists: * Tom Linton, Head of World Wide Sales Engineering, Atlan * Marcela Granados Lavoie, Principal, Global Head of Insurance, Databricks * Zach Taher Vice President, Data Engineering, Northwestern Mutual * Dylan Austin, Vice President, MLOps Engineering, PURE Insurance What one foundational capability must insurers get right in the next two years? The panel's answer was remarkably aligned: All panelists agreed that data quality and governance, paired with intentional information architecture is the most important foundational capability for insurance industry technology and LOB leaders. You cannot build trustworthy AI on untrustworthy data. Invest in the foundations you need for clean, well-defined, well-governed data with rich context attached. What are the larger set of challenges reshaping the insurance industry right now? Trend 1: Human+AI collaboration. Two ideas came forward around human+AI collaboration: AI for augmentation, and trust through transparency. AI for augmentation The panel was clear: underwriters, claims professionals, and agents aren't replaceable. They're essential. At the same time, insurance professionals' impact can - and must - be augmented with AI. AI makes it possible for insurance pros to complete their goals, deliver work that's more consistent, and make better informed decisions. Trust through transparency The discussion highlighted how technology platforms can surface data lineage and business definitions directly within AI-powered workflows. Practitioners can examine the "why" behind a recommendation, not just see and nod along to the output. When end users actively shape AI, trust compounds over time. Trend 2. Data fluidity and intelligent systems. The insurance industry has plenty of data. Data shortage hasn't been a problem in a long time. The problem is data accessibility and trust problem. That problem becomes more challenging with the evolution to more modular ecosystems. Data that is discoverable, well-governed, and that can flow to the right system - at the right time - with the right context attached - is critical for developing insights and driving transformation. Modern platforms like Databricks and Atlan are enabling insurers to connect disparate data sources with the appropriate context to build richer, AI-ready data products. Insurance organizations are still working to address siloed systems that continue to create blind spots that directly impact underwriting accuracy, claims outcomes, and fraud detection. What's the practical starting point? The panel agreed that leaders must invest in discoverability and metadata management before trying to build intelligent systems on top of data you can't find or trust. Trend 3. Ecosystem modularization. Move over monolithic insurance platforms. Here come composable, modular architectures. The panelist conversation reinforced that data solutions are not separate from modernization strategy. They're foundational to making modular ecosystems work and unlocking value across the organization. Rather than rebuilding capabilities system by system, modular ecosystems allow insurers to expose reusable data and analytics building blocks across the enterprise and with partners. This shift also makes it far easier to integrate best-in-class solutions without ripping and replacing core systems like a data catalog, a feature store, or a fraud detection model. Trend 4. Self-directed systems. * Automated underwriting for simple risks * Real-time fraud blocking * Intelligent claims triage These solutions currently exist, but AI is making them more intelligent, adaptable and accessible across lines of business. As these self-directed systems become table stakes, guardrails must be audited to ensure proper decisioning and transparency. "Policy as code," continuous monitoring, explainability frameworks, and clear human escalation paths aren't bureaucratic overhead. Full stop. They are essential in making automation sustainable and auditable. Platforms like Atlan and Databricks are valuable in ensuring self-directed systems perform as intended so they don't drive adverse business outcomes or fail auditability and regulatory requirements. Thank you again to its generous panelists and its community of practitioners at the Data & AI Summit. It was great to be in conversation! | SET AI IN MOTION | | Move AI from experimentation into everyday operations. * Adaptable foundations * Human+AI workflows * Measurable outcomes * $8B+ in customer value * 3x average ROI |

UK Tech News

Jun 26th, 2026

Fivetran selected by Oakbrook Finance to support real-time lending decisions and AI-ready data operations.

Fivetran selected by Oakbrook Finance to support real-time lending decisions and AI-ready data operations. Fivetran, the data foundation for AI, today announced that specialist UK consumer lender Oakbrook Finance has selected the company to centralise and govern data across its analytics estate. The deployment supports customer insight, product development, marketing effectiveness and machine learning workflows, while saving Oakbrook's data engineering team approximately three months of build time. Founded in 2011, Oakbrook is a specialist consumer lender serving near-prime and non-prime borrowers across the UK who are typically overlooked by mainstream banks. The business has lent more than £1.5 billion to UK customers and currently serves around 140,000 active borrowers. A significant share of applications comes through price comparison platforms, where Oakbrook typically has less than 10 seconds to ingest data, run its models, and return an offer. "Our data engineering team is lean and deliberately focused. Before Fivetran, a meaningful chunk of their time was spent maintaining pipelines rather than building things that move the business forward," said Ed Ball, Head of Data and Security at Oakbrook. "Fivetran has let us connect data sources we wouldn't have reached otherwise, which has materially expanded what we can analyse and model, from customer behaviour through to how our products perform in the market. That's directly fed into work like the launch of OakbrookOne, our debt consolidation product." To meet these requirements without increasing operational overhead, Oakbrook adopted an automated approach to data integration. Fivetran enables the company to centralise and govern data from multiple sources, supporting an open data infrastructure model in which data remains accessible, consistent, and under Oakbrook's control. "Financial services organisations are under pressure to move faster while maintaining strict governance and control over their data," said Alex Cresswell, Regional Vice President, Northern Europe, Middle East and Africa (NEMEA) at Fivetran. "An open data infrastructure allows them to do both, by ensuring data is accessible, governed, and usable across systems without adding operational complexity." Fivetran now ingests around 5 million rows of data for Oakbrook each month, creating a consistent, governed data layer across the business. This supports improved customer insight, application development, and marketing effectiveness, including the launch of new products such as OakbrookOne, a debt consolidation loan product that has so far enabled more than £50 million in consolidation lending, with customers saving an average of £110 a month and over 40 percent receiving same-day settlement of their existing debts.

Fivetran

Lead Company Operations Manager

About the job