Senior Data Engineer

Company Description:

Acquis is an independent insurance provider and administrator delivering specialist insurance solutions to the finance and leasing industry. The company designs tailored insurance products for a wide range of clients, including multinational bank-owned funders, manufacturer captive finance companies, and independent providers. Acquis customizes marketing approaches, underwriting options, and programme structures to align with each client’s commercial goals. The business is committed to supporting client success through flexible, scalable solutions. Acquis Insurance Management Ltd is authorized and regulated by the Financial Conduct Authority, providing a strong regulatory and compliance foundation.

Role Description:

This role focuses on designing, building, and maintaining data pipelines and ETL processes that support core insurance, finance, and reporting functions. The Senior Data Engineer will develop and optimize data models and data warehouses, ensuring data quality, reliability, and performance across multiple systems. Day-to-day tasks include collaborating with stakeholders to understand data requirements, implementing data solutions that enable advanced analytics, and establishing best practices for data governance and documentation. The person in this role will also mentor other team members, contribute to technical standards, and work closely with IT and business teams to support strategic projects.

Key Responsibilities:

• Design, build, and maintain scalable, robust data pipelines to ingest, transform, and deliver data from multiple source systems.
• Develop and optimise the enterprise data warehouse to provide a single, trusted source of data across the organisation.
• Reduce reliance on manual data processing by automating data flows, integrations, and transformations.
• Ensure data is accurate, consistent, and reliable through the implementation of data quality checks, monitoring, and validation processes.
• Work closely with BI, analytics, and business stakeholders to understand data requirements and enable high-quality reporting and insight.
• Support the transition to self-service analytics by ensuring data is structured, accessible, and well-governed.
• Design efficient, scalable data models that support both operational reporting and advanced analytics use cases.
• Improve performance, scalability, and cost-efficiency of data processes and infrastructure.
• Integrate new data sources, including operational systems and third-party platforms, into the data platform in a consistent and governed manner.
• Establish and maintain best practices in data engineering, including documentation, version control, testing, and deployment processes.
• Collaborate with Technology and BI teams to align data architecture with overall system architecture and business strategy.
• Stay up to date with emerging data engineering tools, technologies, and best practices to continuously enhance Acquis’ data capability.