Lead Analytics Engineer - Finance Data (FinOps)

Description

The company is the company, and it is growing quickly, so the Finance team needs data that can keep up. The role is a central data team position, reporting to the Head of Central Data, and the team works with every function, with Finance as its main partner.

The Lead Analytics Engineer for Finance is the data partner for treasury, reconciliation and accounting, and supports corporate finance and investor reporting alongside the existing corporate finance data partner.

The work is not limited to delivering tickets. You will learn how Finance operates and why, find where value sits, and work with the team to improve their processes and the data and tools behind them.

The team uses a modern stack, can try new tools, is rewarded for driving change, uses AI assistants for routine work, works in English, and builds data that functions keep developing after handover.

Responsibilities

• Work with the Treasury, Reconciliation and Accounting teams on their processes, priorities and how data can support them.
• Build treasury data covering positions, cash flows and liquidity as data products the team can depend on daily.
• Scale reconciliation so matching, breaks and exceptions are handled through systems instead of manual effort.
• Provide the data, checks and integrations that Accounting needs for the close and routine work.
• Support the corporate finance data partner on corporate finance and investor reporting, using one shared model and common definitions.
• Design and evolve the Finance data model, including entities and metrics, with tests, lineage and documentation so others can reuse and extend it.
• Define data standards and quality checks for Finance, and build integrations with the systems Finance uses.
• Introduce automation and agents into Finance workflows wherever they cut recurring manual work.
• Review current Finance processes, identify improvements, and link each piece of data work to its business cost and value.

Requirements

• You have worked in finance or closely with finance teams, as a finance team member, a finance data partner, or in data work focused on treasury, reconciliation, accounting or FP&A.
• You understand how a finance function runs, including the close, cash and liquidity management, reconciliations and the reports they produce.
• You write advanced SQL and have strong skills in dimensional and semantic data modelling.
• You have built metrics and data products that other teams rely on.
• You have experience with ETL and data warehouse or lakehouse work, including bringing in new sources from start to finish.
• You prioritise precision over speed when they conflict.
• You work as a consultant to the business: you understand a process, propose solutions and explain them in terms of business value.
• Databricks and Unity Catalog.
• Experience integrating ERP, accounting, banking or treasury systems.
• Experience with workflow automation or agents in finance processes.
• CI/CD, orchestration and infrastructure-as-code.
• Background in fintech, banking or payments.

Conditions

You have high autonomy and choose the tools and approach, including trialling new vendors and open-source options.

Sign-off is required for two things: architecture, meaning whether a solution scales, works across use cases and growing volumes, and runs without constant support; and anything that feeds high-stakes decisions.

Priorities are set by final business impact.

Benefits

• Growth path: in the first months you learn Finance, the data model, the stack and your stakeholders; by six months you work independently and make scope and design calls without escalating; after that you set long-term goals with Finance stakeholders, own the treasury, reconciliation and accounting data roadmap, and mentor others in analytics engineering.