VP – Analytics Engineering

Siena Partnership; Greater London; On-site; GBP 221,000 - 277,000; Full time

Job summary

Siena Partnership is building a new Analytics Engineering capability with a VP-level leader who bridges strong engineering foundations and strategic delivery. You’ll shape architecture, oversee data products, and collaborate with senior stakeholders to translate complex business problems into scalable technical solutions.

You will stay close to code and architecture, guiding a 4–10 engineer team and setting standards for data quality, lineage and governance.

Qualifications

• Strong SQL, Python and data modelling skills.
• Experience leading a small engineering team while remaining technically credible.
• Background in engineering environments such as fintech, insurtech or financial services.

Responsibilities

• Lead the technical direction and delivery of a new Analytics Engineering capability.
• Act as the go-to technical voice across architecture, data modelling, engineering patterns and platform design.
• Lead a small engineering team from a technical and delivery perspective.
• Review and challenge engineering decisions to maintain high standards.

Skills

SQL

Python

Data modelling

Leadership

Stakeholder management

Tools

Snowflake

dbt

APIs

CI/CD

Job description

6-month initial contract | Strong extension potential

I’m working with a top-tier global private equity fund that is building a new Analytics Engineering capability within a strategically important area of the business.

This is a genuine build-from-scratch opportunity with the pace, autonomy and influence of a scale-up environment, but with the backing, data and reach of a major global investment organisation.

They are looking for a VP-level Analytics Engineering leader who can combine strong engineering foundations with the ability to lead delivery and operate confidently with senior business and investment stakeholders.

This is not a hands-off Head of Data or transformation role.

You will remain close to the engineering, act as a technical authority for the team, shape architecture and delivery standards, and help translate complex or ambiguous business requirements into high-quality data products.

Key responsibilities

• Lead the technical direction and delivery of a new Analytics Engineering capability.
• Act as the go-to technical voice across architecture, data modelling, engineering patterns and platform design.
• Lead a small engineering team from a technical and delivery perspective.
• Remain close enough to the code and architecture to review, challenge and improve engineering decisions.
• Work directly with senior business and investment stakeholders to understand problems and translate them into scalable technical solutions.
• Build trusted data products across complex financial, investment and insurance datasets.
• Establish strong standards around data quality, reconciliation, lineage, testing and governance.
• Design scalable integrations, data models and production engineering workflows.
• Help shape how AI and automation can improve engineering delivery and data workflows.
• Play a major role in the future structure and growth of the team.

What we’re looking for

• Strong software engineering or data engineering foundations.
• Experience leading a relatively small engineering team while remaining technically credible.
• Strong SQL, Python and data modelling skills.
• Experience building and owning production data platforms or data products end to end.
• The ability to challenge engineers on architecture, modelling, pipelines and production design.
• Strong stakeholder skills and the confidence to operate with senior non-technical audiences.
• Experience taking an unclear business problem and working out the right technical solution rather than simply executing a specification.
• Background in a strong engineering environment such as fintech, insurtech, insurance, investment management or financial services.

Particularly relevant backgrounds

Experience across any of the following would be highly attractive:

• Insurance / insurtech
• Insurance investment or asset-management data
• Fintech
• Private markets
• Fixed income / institutional credit
• Investment management
• Reinsurance / annuities

Direct insurance or private-credit experience is advantageous, but strong engineering foundations are more important than having worked in one exact domain.

Technology environment

• Python
• SQL
• Snowflake
• dbt
• APIs / integrations
• Modern orchestration tooling
• CI/CD
• Data quality, reconciliation and lineage

Heavy dbt experience is not essential at VP level. Strong engineering fundamentals and the ability to quickly understand and challenge a modern data stack are more important.

This could be particularly interesting for someone who has spent the last few years leading a team of around 4-10 engineers and is now ready to step into broader responsibility without moving away from the technology.

A background combining some consulting or client-facing experience with subsequent hands-on engineering in a fintech, insurtech or financial-services business would also be highly relevant.

They do not need a career CDO who has spent years managing very large organisations. They are looking for someone at the point in their career where this represents an exciting step up in responsibility.

£1,200-£1,500 per day, outside IR35. Initial 6-month contract with strong potential to extend and develop into a longer-term opportunity.