Data Product & Analytics Engineering Senior Manager

Manage and develop a team of four Analytics Engineers across different levels of seniority. 

Provide technical direction, coaching and context while creating an environment where engineers retain ownership of solution design and implementation. 

Work with the team on modelling and architecture decisions, challenge proposed approaches, identify opportunities for reuse and simplification, and ensure solutions align with our target data architecture. 

Coach engineers at different levels, helping them improve not only their technical capabilities but also their understanding of business problems, architectural thinking and ownership of data products. 

Define and maintain a prioritised roadmap covering new data models, data marts, dimensions and attributes, governed metrics, and architectural improvements.

Drive the transition towards more centralised and trusted data models, reducing duplicated transformation logic and creating reusable representations of core business entities, facts, dimensions, metrics and relationships. 

Take requirements from problem definition through discovery, architecture, prioritisation, delivery, quality assurance, adoption and ongoing ownership. 

Coordinate dependencies across Product Engineering, Data Engineering, Insights, Reporting and other teams. Ensure upstream changes and ingestion requirements are identified early enough to support downstream data delivery. 

Understand the underlying problem behind stakeholder requests and determine whether the right solution is a new attribute, metric, model, mart or enhancement to an existing data product. 

Someone comfortable building technical solutions as you are communicating them to non technical stakeholders

A strong previously hands-on Data Engineer and/or Analytics Engineer.

A clear communicator with experience translating business problems into scalable data products and technical requirements. 

Excited about fintech and the particular challenges that come with a regulated, app-first, long-consideration financial product.

Comfortable with ambiguity and able to operate with autonomy in a fast-paced environment where the brief sometimes evolves mid-sprint.

5+ years of experience with data architecture and analytical data modelling.

Experience with modern transformation frameworks such as dbt and cloud data platforms such as Databricks, Snowflake or equivalent. 

Experience leading, mentoring or technically guiding Data/Analytics Engineers. 

Understanding of the complete data lifecycle from source applications and ingestion through transformation, semantic modelling and consumption. 

Experience managing roadmaps and prioritising competing business, architectural and technical requirements. 

The ability to communicate comfortably with both engineers and senior business stakeholders. 

Knowledge of data quality, testing, lineage, documentation, ownership and governance practices. 

Experience working in a regulated industry, ideally financial services or fintech, with an understanding of how governance, controls and regulatory requirements influence data architecture and delivery. 

Experience with Databricks and dbt, particularly designing or evolving a centralised transformation/modelling layer. 

Experience managing dependencies across Product Engineering, Data Engineering and Analytics teams, particularly where delivery requires changes to upstream applications or event/data generation.