Senior Data Engineer, N and I Business Operations

Overview

In this Senior Data Engineer role within Home Office Digital, you will design and lead data flows that connect operations with analytics to support government services. You will collaborate with Data Scientists and Product Owners to align data engineering with business needs, mentor juniors, and promote agile ways of working. The role offers exposure to large, varied datasets and opportunities to influence data architecture and service technology. A meaningful hook is the mission to deliver joined-up, intelligent data services that improve public outcomes.

Pay / Benefits

• Civil Service Pension with employer contribution
• In-year reward scheme
• 25 days annual leave
• 8 public holidays + 1 privilege day
• Hybrid working (minimum 60% in office)
• Capability-based allowance (non-contractual)

Responsibilities

• Analyze problems to identify root causes and develop innovative solutions
• Analyze testing activities and support data engineers and stakeholders
• Design and implement a data streaming service and develop new data models and ETL processes
• Ensure successful delivery of data loads for customers and researchers, with troubleshooting as needed
• Build and test data products at large scale across full development lifecycle
• Apply data modelling principles and provide guidance on data models across subject areas

Key requirements

• Extensive finance operations experience in UK government or a large regulated organization with governance and controls
• Budgeting, forecasting, cost allocation, reconciliation, and investigation of discrepancies
• Experience with invoicing, P2P, O2C, AP/AR processes
• Experience with ERP/finance systems such as Oracle
• Ability to communicate complex financial information to both financial and non-financial audiences
• Experience using financial data, spreadsheets, and reporting tools for analysis and decision-making
• Interest in developing technical skills in ETL, automation, programming, and cloud data technologies

• Attention to detail
• Stakeholder communication
• Collaboration and teamwork
• Industry-standard ETL tools
• Data modelling and design
• Data engineering fundamentals

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