Full-Time

Senior Platform Engineer

Platform Infrastructure Engineering

Posted on 9/16/2025

Collibra

Collibra

1,001-5,000 employees

Cloud data governance, catalog, quality platform

Compensation Overview

$152k - $190k/yr

+ Equity Ownership + Bonus Potential

No H1B Sponsorship

Remote in USA

Remote

Candidates must reside in the central USA.

US Citizenship Required

Category
DevOps & Infrastructure (1)
Required Skills
Kubernetes
Microsoft Azure
Python
AWS
Go
Terraform
Google Cloud Platform
Requirements
  • 3+ years of experience in Platform Engineering, SRE, or infrastructure-focused roles with a Bachelor's degree in Computer Science or a related technical field, OR equivalent practical experience demonstrating the skills below.
  • Proven experience designing, building, and managing production services using kubernetes and gitops / IaC at a scale of between tens and hundreds of kubernetes clusters.
  • Experience managing production workloads and infrastructure on major cloud platforms (AWS, GCP, Azure).
  • Hands-on experience operating Kubernetes clusters and managing containerized services in production.
  • Demonstrable experience writing and maintaining Infrastructure as Code (IaC), preferably with Terraform, and proficiency in Golang or Python for automation.
  • Must be eligible to work in the USA without requiring sponsorship.
  • Because this role supports the US government, it is required that this candidate be a US citizen who resides on US soil.
Responsibilities
  • Develop controllers and automations, work with development teams on refinements to platform capabilities.
  • Contribute to the overall architecture of the platform infrastructure, collaborating with other infrastructure engineers using GitOps, IaC and Kubernetes.
  • Participate in on-call rotations, troubleshoot complex service issues, implement security best practices, and maintain clear documentation (architecture, procedures).
  • Stay current with platform engineering trends and infrastructure automation, identifying and implementing improvements.
Desired Qualifications
  • Preferred skills: CKA / CKAD, Istio, ArgoCD, deep experience with networks, linux and Kubernetes, experience with monitoring/logging tools and observability spans / traces (e.g., Datadog, Grafana, Honeycomb), and proficient in creating controllers and other automation patterns to manage Kubernetes resources.

Collibra provides a cloud-based data intelligence platform that combines data governance, data cataloging, data quality, data lineage, and AI governance to help large organizations manage and trust their data. The platform connects data sources, metadata, and policies so users can automate data workflows, catalog assets, track data lineage, monitor quality, and enforce governance rules while staying compliant with regulations like GDPR. What sets Collibra apart is its strong enterprise focus on comprehensive metadata management and governance across the data lifecycle, with modules that cover governance, catalog, lineage, quality and observability, and AI governance, aimed at enterprise-scale deployments and regulated industries. The company's goal is to help organizations find, understand, and trust their data, enabling better decision-making and compliance through scalable data governance and stewardship.

Company Size

1,001-5,000

Company Stage

Series G

Total Funding

$601.7M

Headquarters

New York City, New York

Founded

2008

Simplify Jobs

Simplify's Take

What believers are saying

  • AI trust gap drives 84% of decision-makers to increase spending on governance solutions.
  • Partnerships with Giskard and Nexer expand AI testing and master data management integrations.
  • Integrations with Azure AI Foundry and MLflow broaden model governance capabilities.

What critics are saying

  • Alation erodes market share with simpler search, causing 40-60% defection in 12-18 months.
  • Microsoft Purview bundles governance in Azure, triggering 20-30% churn in 6-12 months.
  • Platform complexity abandons 25% of pilots due to steep learning curves.

What makes Collibra unique

  • Collibra's AI Command Center provides real-time oversight for agentic AI systems.
  • Deasy Labs acquisition enables unified governance of structured and unstructured data.
  • AI Copilot accelerates asset discovery via natural language queries for all users.

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

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Mental Health Support

Unlimited Paid Time Off

Flexible Work Hours

401(k) Retirement Plan

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

-1%
HPCwire
Mar 31st, 2026
The AI trust gap: why AI performance requires control.

The AI trust gap: why AI performance requires control. by Felix Van de Maele | March 31, 2026 Press play to listen to this content For the past few years, the corporate world has been locked in an AI race. Every company is trying to move faster, invest more and keep up with the pace set by Big Tech. But speed isn't the only challenge. We've reached a point where capital investment is outpacing organizational confidence. A new survey from Collibra, in partnership with The Harris Poll, reveals a clear contradiction at the heart of enterprise AI: 84% of technology decision makers say they must increase AI spending this year to remain competitive with Big Tech, yet 88% admit their organizations are still not using AI to its full potential. More investment, less confidence. This is the AI trust gap, the fundamental disconnect between the desire to deploy AI and the ability to stand behind its outputs. And it's not just a boardroom issue. Data from YouGov shows that while more than a third of Americans now use AI weekly, only 5% say they have a lot of confidence in it. We have a world that is using AI but not yet trusting it and spending alone can't fix that. Performance requires control. AI systems are already capable of generating insights, recommendations and decisions quickly, and at scale. The issue is not capability, it's control. Our research makes this clear. 89% of leaders say they can't have full confidence in AI insights until the underlying data is trusted and verified. If the data behind AI is incomplete, unverified or disconnected from business context, the output becomes unreliable. And when outputs can't be trusted, they have to be checked. That control doesn't happen by default, it comes from governance. Governance defines the data, context and boundaries AI systems operate within, ensuring outputs are accurate, safe and aligned. Without it, AI doesn't scale decisions, it scales uncertainty. The human in The loop: tasks move, accountability doesn't. That lack of trust has a direct cost. According to our Harris Poll research, more than half of decision-makers (55%) say they at least sometimes need to correct or push back on AI-generated outputs. That's not a minor inconvenience, it's executive time being spent on quality control instead of strategy. It also highlights a distinction that often gets lost in the debate about AI and jobs: the difference between a task and a job. AI can take on repetitive, data heavy tasks but it can't take on accountability. The public already understands this. 68% of Americans say they would never trust an AI system to act on their behalf without reviewing each action first. When an executive uses AI to generate a complex report, the technology handles a task that was once a manual burden. But if that executive is still reviewing every line for errors and hallucinations, the burden of responsibility hasn't moved. The machine completed the labor. The job stayed human. Bridging the AI trust gap means getting past that cycle, so leaders can stop supervising outputs and get back to making the decisions that actually matter. The new red flag for 2026. The AI trust gap is also redefining what competence looks like. Our research found that 64% of decision makers already consider it a red flag when candidates lack familiarity with AI tools. But familiarity is quickly becoming table stakes. As we move further into 2026, the real red flag will be leaders who can't tell the difference between outputs that look right and outputs that are right. Knowing how to prompt a model is one thing. Understanding whether the data behind it is reliable, governed and verified is another. That distinction is where AI literacy is heading, and organizations that don't build this capability into their culture will struggle to assess risk or realize the value of the systems they're investing in. Closing the gap. The path to AI ROI doesn't start with a bigger budget. It starts with control. The findings from our Harris Poll research is clear: investment without trust creates expensive uncertainty. And trust doesn't happen by default. It has to be built into how AI systems operate. Organizations that will pull ahead in 2026 are those that pair their AI ambitions with trusted data, strong governance and the ability to evaluate what AI produces. That's when the trust gap closes. That's when AI systems stop stalling and start delivering real performance. And that's when AI starts being a true competitive advantage. About the author: Felix Van de Maele is Founder and CEO of Collibra. He has led Collibra for more than ten years of record growth and is responsible for global business strategy. Prior to co-founding Collibra, he served as a researcher at the Semantics Technology and Applications Research Laboratory (STARLab) at the Vrije Universiteit Brussel, where he focused on ontology-focused crawlers for the semantic web and semantic data integration. If you want to read more stories like this and stay ahead of the curve in data and AI, subscribe to BigDataWire and follow us on LinkedIn. We deliver the insights, reporting, and breakthroughs that define the next era of technology.

Danir
Jan 28th, 2026
NEXER PARTNERS WITH COLLIBRA TO STRENGTHEN DATA & AI

Nexer partners with Collibra to strengthen Data & AI. Nexer has entered a new partnership with Collibra, a leader in data intelligence and data governance. The collaboration strengthens Nexer's Data and AI capabilities by adding a leading platform for data and AI governance, data cataloguing and data quality, complementing Nexer's existing strengths in data platforms, integrations, analytics and master data management. Nexer supports organisations in building robust and scalable data foundations for AI and data-driven services, spanning data platforms, integrations, analytics and master data management. As AI adoption accelerates, organisations are increasingly focused on establishing data transparency with access to trusted, well-governed data that can be used consistently across the enterprise. "AI initiatives are only as strong as the quality and trustworthiness of the data behind them," says Jesper Leth, Director Data Strategy and Product Management at Nexer Data Management. "Master data management provides a critical foundation, and Collibra adds the governance and data intelligence layer that makes business-critical data easier to find, understand and use across the organisation." Collibra provides organisations with a central platform to catalogue, govern and monitor data and AI assets across multiple systems and environments. When combined with Nexer's master data management solutions and data platform capabilities, organisations gain a governed data foundation that supports AI, analytics and data-driven innovation at scale. "Many organisations feel pressure to deliver AI use cases quickly, but sustainable results depend on having control, transparency and trust in the underlying data," continues Jesper Leth. "By combining Nexer's Data and AI capabilities with Collibra's data intelligence platform, we help organisations operationalise data governance and create reliable, AI-ready data foundations." Read more about the solution and Nexer's offering on Collibra here. About Nexer Nexer Data Management is part of Nexer Group - an international tech company with roots in Swedish entrepreneurship and innovation. With experts in Data & AI, data management, system integrations, data analytics, digital transformation, enterprise applications, IT and R&D, Nexer helps organisations across the globe turn data and technology into real business value. Nexer is part of the privately owned Danir Group. About Collibra Collibra frees your data from the constraints of silos by unifying data and AI governance across every system and bringing business and technical users into the fold. It gives you a higher degree of compliance paired with more autonomy, so your users can trust, comply and consume. Accelerate and strengthen every data and AI use case. About Nexer. Nexer is a tech company deeply rooted in the Swedish heritage of entrepreneurship and innovation, with a global presence and delivery. Nexer has kept customers one step ahead for over 30 years, with cutting-edge services in strategy, technology and communication. Today, some of the largest, most demanding companies in the world rely on Nexer's dedication and expertise within digitalisation, IT, engineering and R&D. The company has long-term partnerships with market-leading platform providers such as Microsoft, IBM, Stibo and others. Nexer has 2500 experts in 15 countries. The company is a part of the Danir group, a Swedish privately held company with 12,000 employees in 18 countries.

TechTarget
Oct 21st, 2025
Immuta adds provisioning prowess to speed insight generation

Immuta adds provisioning prowess to speed insight generation. Featuring automation capabilities, the new tools dramatically reduce the time it takes to operationalize governed data and could help differentiate the vendor from its peers. Immuta on Tuesday introduced new data provisioning capabilities designed to better enable customers to access and deliver governed data to agents and other applications. Data provisioning is the process of making data available precisely when and where it is needed. It includes collecting data from disparate sources, preparing and transforming the data so it can be consumed, and delivering it to its proper target destination. Immuta's new features, which include automation capabilities, aim to reduce what has historically been a weeks-long, manual provisioning process down to minutes. They include Guardrail Policies to put governance measures in place that automate access to data, Policy Exception Workflow to enable users to ask for exceptions through a structured workflow rather than ad hoc requests, and Multi-Approver Setup to help data owners and governance teams automate data provisioning policies. Guardrail Policies and Multi-Approver Setup are generally available while Policy Exceptions Workflow is in public preview. In addition, Immuta made Marketplace, a governed hub where users can discover and provision data assets, generally available. Given that real-time decision-making is crucial to many businesses, and agents need diverse real-time data to properly behave, Immuta's new features are "highly significant" for the vendor's users, according to Stephen Catanzano, an analyst at Omdia, a division of Informa TechTarget. "The combination of guardrails, exception handling and multi-approver capabilities with the Marketplace creates a complete end-to-end system that can handle policy-driven automatic approvals and request-based access in one platform, which is particularly crucial as AI exponentially multiplies data access requests," he said. Based in Boston, Immuta is a data governance and security vendor that competes with specialists including Satori and Privacera and broader-based data management vendors with governance capabilities such as Alation, Collibra and Informatica. Powering provisioning. Historically, data-driven decision-making had plenty of lag time. Data was often controlled by a central team, and requests for reports and other data assets generally took weeks - sometimes months - to fulfill. The rise of self-service analytics around 2010 changed that to some degree, but weekly, monthly and quarterly reports were still the basis for many of the insights that led to decisions and actions. Worldwide events beginning in 2020 such as the COVID-19 pandemic, the war in Ukraine, repeated supply chain disruptions and economic uncertainty radically altered the speed that decisions had to be made, placing greater emphasis on real-time data. Surging interest in AI, sparked by OpenAI's November 2022 launch of ChatGPT, has only heightened the emphasis on real-time decision making. Reducing what had been a time-consuming provisioning process down to minutes is therefore crucial, according to William McKnight, president of McKnight Consulting. "Immuta's Marketplace and structured workflows accelerate secure data provisioning at enterprise scale, eliminating the bottleneck that slows analytics and AI initiatives," he said. "By automating fine-grained access controls across cloud platforms, Immuta enables faster data use by both human users and AI agents without compromising security." Perhaps the most valuable new feature is Guardrail Policies, McKnight continued. "While the Marketplace delivers the speed, the Guardrail Policies stand out as crucial for governance teams because they ensure the integrity and safety of the system, allowing the rapid speed afforded by the Marketplace to be sustainable at scale," he said. Catanzano likewise called out Guardrail Policies. But while McKnight noted that the feature fosters speed and scale, Catanzano highlighted its preventative nature, particularly with AI agents capable of taking on tasks without human involvement. Beyond the individual features that comprise Immuta's improved data provisioning capabilities, the suite is designed to integrate with data catalogs and other governance platforms to further speed and simplify the provisioning process. The rise of generative AI (GenAI) and AI agents provided Immuta with the impetus for developing its new capabilities, according to Matt Carroll, the vendor's CEO. GenAI has enabled more people within organizations to work with data, he noted. However, in doing so, it has also exposed enterprises to a greater risk of data breaches and regulatory noncompliance. "With so many new data consumers, the challenge becomes how to make data discoverable and accessible while still enforcing the right policies and controls," Carroll said. "That's what led us to develop data provisioning workflows." While valuable for Immuta's users, whether the new data provisioning capabilities can help the vendor stand out from its competitors remains to be seen, according to Catanzano. Immuta's new features comprise a unified data provisioning workflow that automates processes that previously took significant time, but vendors such as Informatica also provide data provisioning capabilities, he noted. "Immuta's focus on AI-scale access requests may differentiate it from traditional governance tools that weren't built for dynamic, high-volume environments," Catanzano said. "But... I don't think it's a major differentiator. All the major players moving and governing data have a strong story here, but with some nuances." McKnight similarly mentioned speed as a way Immuta might separate from other vendors. While many provisioning platforms show users what data exists and allow them to request access, Immuta's automates secure provisioning. "Immuta automatically applies the right policies - masking, filtering, anonymization - at query time across cloud platforms," McKnight said. "It's the difference between discovering data and actually getting governed access to it in minutes [rather than] weeks." Next steps. Looking ahead, Immuta is planning to add native integrations with data warehouses and database platforms to make it easy for customers to access data where it lives, according to Carroll. In addition, the vendor plans to deepen partnerships with data catalogs, add conversational interfaces to simplify using its tools and launch its Agentic Data Governor, he continued. "Thematically, 2025 and early 2026 are about expanding connectivity, embedding Immuta wherever data is discovered, bringing governance into conversational AI, introducing native AI to accelerate access and decision-making and delivering intelligent, customer-specific governance agents that redefine what secure, automated data provisioning looks like," Carroll said. Focusing on AI governance capabilities with tools such as the Agentic Data Governor is wise, according to McKnight, who noted that while the new data provisioning tools advance one part of Immuta's platform, others also need improvement. "The company must advance its GenAI governance by building dynamic prompt and output controls that detect and protect sensitive data in [large language model] interactions in real time," McKnight said. In addition, adding native connectors to broaden its data integration capabilities and evolving from alert-based monitoring of policy violations to automated remediation are ways Immuta could better serve its users, he continued. Catanzano, meanwhile, suggested that Immuta add AI-powered capabilities to its provisioning suite, among other ways the vendor could potentially advance its offerings. "Immuta could expand into AI-native features like intelligent policy recommendations based on usage patterns or real-time data quality scoring within the provisioning workflow to ensure AI systems get not just governed data, but high-quality governed data automatically," he said. Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than 25 years of experience. He covers analytics and data management.

Collibra
Jul 29th, 2025
The end of governing "everything": A smarter approach with Data Usage

Collibra is excited to introduce Data Usage for Snowflake, a powerful new capability designed to bring clarity and focus to your data strategy.

Collibra
Jul 29th, 2025
Integrating Collibra with Azure AI Foundry and MLflow: New integrations expand scope of model governance

Collibra now integrates directly with Azure AI Foundry and MLflow, two widely adopted platforms for model development and management.

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