Head of Analytics Engineering
New
UKFull-TimeManager
Salary not disclosed
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Job Details
- Required Skills
- Snowflakedbt
Requirements
- Have significant experience leading teams of senior engineers, with a track record of building and scaling high-performing analytics engineering groups.
- Can demonstrate strategic ownership of a technical domain: setting direction, driving alignment, and delivering measurable outcomes at group or department level.
- Have a strong product mindset for data: you think about data assets in terms of consumers, quality, ownership, and discoverability, not just pipelines and models.
- Are an exceptional communicator with proven senior stakeholder management skills, including the ability to influence without authority, manage competing priorities transparently, and turn complex technical context into clear business language.
- Have deep expertise in modern analytics engineering (DBT, Snowflake, Fivetran or equivalent) and can provide strong technical oversight without being hands-on day-to-day.
- Take a structured, principled approach to data governance: you have experience driving alignment on definitions, establishing ownership frameworks, and raising the bar on data quality at scale.
- Are familiar with AI coding assistants (such as GitHub Copilot, Cursor, or similar) and understand how they can meaningfully improve engineering productivity within an analytics engineering context.
- Have a working knowledge of semantic layers (such as dbt Semantic Layer, Cube, or LookML) and understand how they underpin reliable, consistent data access, including their role in enabling AI tooling and MCP-based data discoverability.
- Are passionate about developing people and building systems, processes, and cultures that enable others to do their best work.
- Are proactive, self-aware, and continuously looking for ways to improve both yourself and the organisation around you.
Responsibilities
- Lead a dynamic team, working closely with various business units to translate complex business requirements into actionable data solutions.
- Play a critical role in communicating analytics insights clearly and with impact, enabling data-driven decision-making across the organization.
- Define and own the multi-year technical vision and strategy for Analytics Engineering, ensuring alignment with Paddle's product and business objectives.
- Lead, coach, and develop a team of Senior Analytics Engineers, fostering a high-performing, inclusive, and growth-oriented culture.
- Drive and champion best practices in analytics engineering, data modelling, data governance, and operational excellence across all teams.
- Serve as the senior Engineering representative for Analytics Engineering with cross-functional leaders in Product, Finance, Sales, Marketing, and Data Platform.
- Champion a product mindset for data across the organisation: ensuring Paddle's analytics data estate is treated as a first-class product with clear ownership, defined consumers, and measurable quality standards.
- Lead the definition and governance of shared data definitions and business metrics, working cross-functionally to drive alignment and eliminate ambiguity across teams.
- Own the prioritisation of the Analytics Engineering roadmap, balancing strategic data product initiatives, platform reliability, data quality improvements, and stakeholder requests in a structured and transparent way.
- Oversee the reliability, scalability, and accuracy of Paddle's analytics data estate, including core data pipelines, data models, and transformation layers (Snowflake, DBT, Fivetran).
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