Senior Engineering Manager - Data Delivery

What You'll Do

• Lead, mentor, and grow Engineering Managers and senior engineers across both teams, building a high-performing oranization capable of scaling with the business.
• Own hiring, performance management, and career development across your department, investing in individuals at every level and fostering a culture of engineering excellence and psychological safety.
• Establish clear goals, team rituals, and execution cadences across a geographically distributed organisation, ensuring alignment, accountability, and high-quality delivery.
• Develop and execute on organisational priorities, workforce planning, and department-level objectives in partnership with senior leadership.
• Set the technical direction and roadmap for both teams, establishing operational objectives, guiding architectural evolution, and ensuring each platform scales reliably to meet current and future business demands.
• Guide the frontend platform team as the owner of Samba’s unified internal UI platform, holding the bar on platform integrity, shared component quality, and the developer experience for teams building on top of it.
• Drive the data delivery team’s architectural strategy through a major system re-architecture, eliminating single points of failure, building toward a lightweight, extensible pipeline model, and expanding delivery capabilities to new data types and clients.
• Own the technical direction for pipeline reliability, data quality, SLA management, and the API layer that bridges backend data systems with frontend tooling.
• Oversee full-stack delivery across the organisation, spanning React-based frontend platforms, RESTful API design and maintenance, and backend data processing systems, ensuring clean contracts between layers and sound architectural decisions across the stack.
• Champion engineering best practices across both teams: observability, CI/CD, incident management, on-call health, data quality frameworks, and testing coverage.
• Participate in department-level and cross-org architectural discussions, representing Data Delivery’s constraints, requirements, and roadmap to senior stakeholders.
• Partner closely with Product Management to translate business strategy into engineering roadmaps, navigate trade-offs, and ensure predictable delivery across both teams.
• Collaborate with Data Science, Platform Engineering, and commercial teams to ensure both platforms are well-integrated, well-governed, and fit for purpose across all downstream use cases.
• Engage Business Development and commercial stakeholders to support partner integrations and evolving data delivery requirements.
• Serve as the primary technical voice for Data Delivery with senior leadership, communicating roadmap progress, risks, and strategic opportunities clearly, and persuading stakeholders across functions on departmental priorities.
• Drive predictable, high-quality delivery across multiple concurrent workstreams, balancing active platform development against significant ongoing operational and KTLO responsibilities across both teams.
• Own operational reliability for both platforms, including on-call practices, incident response, post-mortems, PagerDuty SLA management, and the active effort to reduce operational load over time through system maturity.
• Define and enforce data quality and observability standards for data delivery pipelines, ensuring accuracy and integrity of all data feeds delivered to clients and partners.
• Own the department budget, driving cloud cost efficiency and resource allocation decisions, including Databricks compute optimization, with a clear view of business impact.

Who You Are

• 10+ years of software engineering experience, with 4+ years in engineering management including proven experience as a second-line manager leading Engineering Managers across multiple teams.
• Strong command of full-stack system design, API design and maintenance (REST, GraphQL, or equivalent), clean backend-to-frontend contracts, and the architectural considerations of exposing data systems through service layers to end-user interfaces.
• Technical credibility across both frontend platform engineering (component architecture, design systems, micro-frontend patterns, modern build tooling) and large-scale data infrastructure (distributed processing with PySpark/Spark on Databricks, workflow orchestration with Airflow, cloud data services on AWS), with the ability to engage meaningfully with engineers on each side.
• Experience managing teams with high operational and KTLO load alongside active product delivery, able to protect delivery capacity, make operational work visible, and drive systemic improvements that reduce toil over time.
• Proven ability to set and enforce engineering standards across teams: CI/CD maturity, observability and alerting (e.g. Sentry, Prometheus, PagerDuty), data quality frameworks, and testing coverage.
• Demonstrated ability to establish operational objectives and policies for a department, manage complex multi-team delivery end-to-end, and be accountable for production systems and SLAs.
• Exceptional mentor and coach, you develop managers and senior engineers, build strong feedback cultures, and create leaders capable of operating with autonomy.
• Outstanding communicator across all levels, able to translate complex technical decisions for senior leadership, align diverse stakeholders in ambiguous situations, and represent your teams with clarity and credibility.
 
Preferred
 
• Experience in ad tech, data licensing, or media technology, familiarity with data feed delivery, audience segmentation, or programmatic data flows.
• Hands-on background building or evolving internal tooling platforms, web applications that serve business operations teams, with backend APIs over data systems and frontend interfaces for non-technical users.
• Experience with FinOps practices and driving meaningful cloud cost optimisation, particularly around Databricks or Spark compute.
• Familiarity with data privacy regulations (GDPR, CCPA) and their practical engineering implications.
• Track record of managing geographically distributed teams across multiple time zones.