Data Engineering
Summary
Build and maintain scalable lakehouse data pipelines for a leading insurance firm, using Spark, Python, and Delta Lake to support financial reporting, regulatory compliance, and analytics in a regulated environment.
Our client, a leading insurance organisation, is looking for a forward-deployed Finance Data Engineer to support the modernisation of its Finance data and reporting landscape.
This role sits within the Group Finance function and works closely with Finance stakeholders to design and productionise scalable lakehouse data solutions across multi-cloud platforms. You will play a key role in building trusted, governed data products that support financial close, planning, management reporting, regulatory reporting and advanced analytics.
The ideal candidate combines strong data engineering expertise with solid understanding of Finance processes within a regulated insurance environment.
Key Responsibilities
Partner directly with Finance stakeholders to translate reporting, regulatory and performance management requirements into scalable data solutions.
Design and build robust data pipelines and curated datasets using Spark, SQL, Python and Delta-based lakehouse architecture.
Develop structured bronze, silver and gold layer data products aligned to governance and control standards.
Integrate Finance data from enterprise systems, cloud platforms, APIs and external sources using secure and reusable design patterns.
Deliver governed, analytics-ready datasets for BI tools, SQL environments and AI-enabled query interfaces.
Implement orchestration, monitoring, reconciliation and data quality frameworks to meet Finance control expectations.
Apply strong metadata, lineage and access management practices to ensure data security and auditability.
Support the deployment of governed data applications and structured self-service analytics environments.
Contribute to CI/CD, DevOps practices, documentation and operational handover to ensure long-term supportability.
Candidate Profile
5-8 years of hands-on data engineering experience, preferably within insurance, financial services or another regulated industry.
Strong experience with Spark, SQL, Python and modern lakehouse architectures in production environments.
Proven track record building scalable batch or incremental data pipelines.
Experience implementing data governance, lineage, access controls and secure data publishing practices.
Hands-on experience with Azure and/or Google Cloud data platforms, including storage, orchestration and integration patterns.
Exposure to AI-enabled analytics environments or curated semantic data layers is advantageous.
Solid understanding of Finance processes including financial close, planning, management reporting, reconciliations and regulatory reporting (e.g., insurance reporting requirements).
Strong stakeholder engagement skills with the ability to operate between business and technical teams.
Relevant cloud or data certifications are a plus.
Why Consider This Opportunity?
Join a leading insurance organisation undergoing data and Finance transformation.
Work on modern cloud and lakehouse platforms within a highly regulated environment.
Play a pivotal role in building trusted Finance data products that directly support strategic decision-making and regulatory compliance.
Gain exposure to cross-functional stakeholders and enterprise-wide transformation initiatives.