Data Product & Analytics Engineering Senior Manager
Reads like a Data Leadership role: running a data team.
London Office
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type Full Time
Employment type in the employer’s posting: Full Time
From the employer’s posting
Before you apply
- Eligibility
At this time we cannot offer visa sponsorship for this role and we cannot consider overseas applications. — eligibility source
At this time we cannot offer visa sponsorship for this role and we cannot consider overseas applications.
Read the full posting
What you’ll work on
Full postingManage and coach four Analytics Engineers at different seniority levels
Own and prioritise the analytics engineering roadmap for models, marts and metrics
Drive a shift to centralised, trusted data models and reusable business metrics
Take data products end-to-end from requirements through delivery and adoption
Coordinate dependencies with Product Engineering, Data Engineering and Insights teams
From the employer’s posting
Manage and develop a team of four Analytics Engineers across different levels of seniority.
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
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.
What you’ll bring
All qualificationsCore experience
- 5+ years of experience with data architecture and analytical data modelling.
- Knowledge of data quality, testing, lineage, documentation, ownership and governance practices.
- Experience with modern transformation frameworks such as dbt and cloud data platforms such as Databricks, Snowflake or equivalent.
- 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 leading, mentoring or technically guiding Data/Analytics Engineers.
- Experience with Databricks and dbt, particularly designing or evolving a centralised transformation/modelling layer.
Qualification wording
5+ years of experience with data architecture and analytical data modelling.
Knowledge of data quality, testing, lineage, documentation, ownership and governance practices.
Experience with modern transformation frameworks such as dbt and cloud data platforms such as Databricks, Snowflake or equivalent.
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 leading, mentoring or technically guiding Data/Analytics Engineers.
Experience with Databricks and dbt, particularly designing or evolving a centralised transformation/modelling layer.
Tools in this posting
- Databricks
- dbt
- Snowflake
Source — Tool mentions in context
- 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.
- 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.
About Moneyboxapp
At Moneybox, our mission is to give everyone the means to get more out of life.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 3, 2026 · 27 days ago
- Recorded sightings
- 21
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
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Job 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
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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.
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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.
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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.
Lead the Analytics Engineering team
Own the Analytics Engineering roadmap.
Own data products end-to-end.
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
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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.
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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.
Essential
If you meet most but not all of the above, we’d still encourage you to apply.
Desirable
Employment type
Full Time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
London Office
Working Policy: We have a hybrid policy that includes 2 days from our London office and 3 from home. If the role states it is either hybrid or remote candidates must be based within the UK. Visa Sponsorship:
- Work authorization
We have a hybrid policy that includes 2 days from our London office and 3 from home. If the role states it is either hybrid or remote candidates must be based within the UK. Visa Sponsorship: At this time we cannot offer visa sponsorship for this role and we cannot consider overseas applications. Please read before you apply!
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