Data Product & Analytics Engineering Senior Manager
Description
Job Brief
We’re looking for a Data Product & Analytics Engineering Senior Manager to join the Data & Insight team on a permanent basis. This role is dedicated to lead a team of four Analytics Engineers and own the roadmap for the development of our analytical data products.
You will be responsible for identifying, shaping and prioritising the data capabilities we need, orchestrating their delivery across multiple teams, and leading the Analytics Engineers who will design and implement them. This role combines Data Product Management, Analytics Engineering leadership and data architecture.
What you'll do
Lead the Analytics Engineering team
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Manage and develop a team of four Analytics Engineers across different levels of seniority.
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Provide technical direction, coaching and context while creating an environment where engineers retain ownership of solution design and implementation.
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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.
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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.
Own the Analytics Engineering roadmap.
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Define and maintain a prioritised roadmap covering new data models, data marts, dimensions and attributes, governed metrics, and architectural improvements.
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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.
Own data products end-to-end.
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Take requirements from problem definition through discovery, architecture, prioritisation, delivery, quality assurance, adoption and ongoing ownership.
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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.
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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.
Who you are
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Someone comfortable building technical solutions as you are communicating them to non technical stakeholders
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A strong previously hands-on Data Engineer and/or Analytics Engineer.
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A clear communicator with experience translating business problems into scalable data products and technical requirements.
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Excited about fintech and the particular challenges that come with a regulated, app-first, long-consideration financial product.
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Comfortable with ambiguity and able to operate with autonomy in a fast-paced environment where the brief sometimes evolves mid-sprint.
Experience and skills
Essential
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5+ years of experience with data architecture and analytical data modelling.
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Experience with modern transformation frameworks such as dbt and cloud data platforms such as Databricks, Snowflake or equivalent.
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Experience leading, mentoring or technically guiding Data/Analytics Engineers.
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Understanding of the complete data lifecycle from source applications and ingestion through transformation, semantic modelling and consumption.
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Experience managing roadmaps and prioritising competing business, architectural and technical requirements.
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The ability to communicate comfortably with both engineers and senior business stakeholders.
If you meet most but not all of the above, we’d still encourage you to apply.
Desirable
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Knowledge of data quality, testing, lineage, documentation, ownership and governance practices.
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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.
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Experience with Databricks and dbt, particularly designing or evolving a centralised transformation/modelling layer.
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Experience managing dependencies across Product Engineering, Data Engineering and Analytics teams, particularly where delivery requires changes to upstream applications or event/data generation.
Skills
As published by lever · 9 questions · 2 written answers
Basics
Resume/CV, Full name, Pronouns, Email, Phone, Current location, Current company, LinkedIn URL, Twitter URL, GitHub URL, Portfolio URL, Other website, I identify my ethnicity asSelect all that apply, What gender do you identify as?, Do you consider yourself to have a disability?The information in this form is for monitoring purposes only. If you believe you need a ‘reasonable adjustment’, then please discuss this with your People Team contact who is running the recruitment process., Do you have caring responsibilities?, What type of school did you attend between the ages of 11 and 16?, Do you consider yourself the first person / generation in your family to go to university?
Short answers (4)
- Please provide further details regarding your Right to Work status (e.g., British/Irish Citizen, or specific visa type). If you are currently on a visa, please include the expiry date/renewal date.
- When are you available to start? (e.g. notice period duration)
- What is your expected salary?
- Where did you hear about this vacancy?
Pick from a list (3)
- Do you currently have the Right To Work in the UK?
- Would you require sponsorship to work in the UK? optional
- Do you have hands-on, professional experience building and maintaining data models in dbt?
Written answers (2)
- Please note that if you progress to a google hangouts video interview, the session may be transcribed using AI for note-taking and feedback purposes. The transcript of the meeting will be securely deleted after the recruitment process has ended. Please confirm that you consent to this. You are able to withdraw consent at any time during the recruitment process.
- Which other modern data transformation frameworks or infrastructure have you worked with, such as Databricks or Snowflake?