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ZopaAnalytics Engineering Manager
Zopa is looking for a manager to lead its central analytics engineering group in London. The group serves the whole company rather than one product area,…
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About This Role
Zopa is looking for a manager to lead its central analytics engineering group in London. The group serves the whole company rather than one product area, and demand for dependable, ready-made datasets has grown considerably. Its working relationships extend to Analytics, Data Engineering, Product and Engineering colleagues. The post is full time and hybrid, with two to three office days each week. Headcount in the group is rising, which means…
Job Description
Zopa is looking for a manager to lead its central analytics engineering group in London. The group serves the whole company rather than one product area, and demand for dependable, ready-made datasets has grown considerably. Its working relationships extend to Analytics, Data Engineering, Product and Engineering colleagues. The post is full time and hybrid, with two to three office days each week.
Headcount in the group is rising, which means more hands-on leadership and development time for the manager. The role also has a say in how standards, tooling and working habits evolve as the company's data and AI capabilities mature. People in the group are described as warm, dependable and largely self-managing, and the expectation is quick delivery of high-quality output.
In practice the manager coaches staff, gives frequent feedback and handles performance questions. The manager decides the order of work across incoming requests, strategic projects, capacity and longer-term programmes, and sets a plan for the function that lines up with Product and wider business priorities.
Another strand is improving the reliability, quality and growth potential of analytical data assets, and instilling sound practice in modelling, verification, monitoring, written documentation and automated deployment. The manager also explains the function's role in engineering forums and encourages the use of AI to assist development work.
Responsibilities
- Guide and grow the group toward consistently strong results
- Provide frequent feedback, back development and manage performance fairly
- Decide the order of work across requests, strategic projects, capacity and longer-term programmes
- Write a function plan that matches Product and business objectives
- Strengthen how dependable and scalable the data products are
- Set expectations for modelling, verification, monitoring, documentation and automated deployment
- Work with Product, Engineering, Analytics and business colleagues to produce tangible value
- Help the wider data platform cohere by working with the Analytics, Data Science and Data Engineering functions
- Speak up for good data practice in engineering discussions
- Foster knowledge sharing and experimentation with AI-supported development
Requirements
- Track record of leading teams in analytics engineering, business-intelligence engineering or data engineering
- Earlier experience doing analytics engineering work hands-on as an individual contributor
- A history of building and nurturing high-performing groups
- Strong command of SQL and data structuring, with experience using dbt or similar transformation tools
- Hands-on use of cloud warehouses like Snowflake, BigQuery or Databricks
- Ability to set a technical plan and show concrete business results
- Influence with technical and non-technical stakeholders, and the ability to earn their trust
- Familiarity with testing, observability, documentation and deployment automation
- Technical depth to pinpoint structural problems and work with senior engineers on fixes
- Capacity to lead an independent team without micromanaging
Qualifications
- Creating semantic or metrics layers
- Using AI within analytics engineering or producing data products that are ready for AI use
- Working with orchestration and ingestion tools like Airflow, Dagster or Fivetran
- Scripting in Python for automation or data pipelines
- Experience inside a regulated bank or lender, or another data-driven organisation
- Snowflake know-how, which the posting notes Zopa values
Core Skills
Benefits
- Flexible working arrangements
- Working overseas for as many as 120 days a year, if the right to work applies in that country
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Where is the Analytics Engineering Manager role based?
The role is based in London and is hybrid, with two to three office days each week.
Which tools does the posting mention?
It asks for strong SQL and dbt experience and work with Snowflake, BigQuery or Databricks, and it lists Airflow, Dagster, Fivetran and Python as bonus skills.
What salary does the posting offer?
The posting does not state a salary.
Is the role full time?
Yes, the posting lists the position as full time.
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