About the role

This role will be based in National Data Quality Improvement Service (NDQIS) team. NDQIS is a national service for policing that uses rule based to improve the quality, consistency and comparability of police recorded crime data submitted to the Home Office.

 As a Lead Data Engineer, you will be responsible for designing, delivering and supporting high-quality end-to-end data solutions that enable effective data-driven decision making. Working across the full delivery lifecycle, you will translate complex business requirements into robust, scalable and secure data pipelines, ensuring compliance with Home Office data quality, governance and security standards.

You will lead the design and implementation of complex data integrations and text analysis methodologies, ETL processes and automated workflows, bringing together information from multiple internal and external sources. Working closely with technical and business stakeholders, you will ensure solutions are reliable, resilient and aligned with organisational objectives.

You will shape and implement the data engineering vision and roadmap, promoting best practice, innovation and continuous improvement. Driving automation and championing data quality, you will ensure solutions remain maintainable, cost-effective and scalable. You will build strong relationships across technical and non-technical communities, influencing decision-making and ensuring services align with organisational priorities and user needs.

Where business needs allow, some roles may be suitable for a combination of office and home-based working. Where this is the case, employees will be expected to spend a minimum of 60% of their working time in the office. Applicants can raise any queries to the email address at the bottom of the advert.   

Watch this short video to hear from members of Home Office Digital talking about the projects they work on and their experience of working here: Working for Home Office Digital. 

Job description

Lead Data Engineers deliver the data engineering vision for the organisation as set by the Principal Data Engineer. As a Lead Data Engineer, you will focus on designing and implementing numerous complex data flows to connect operational systems, data for analytics and BI systems.

You will identify and deliver new data sources and develop ETL processes, collaborate with the Data Acquisition, Analytics and Infrastructure teams to deliver the data strategy through the design and implementation of technology systems.

You will lead the data management and data engineering services and analytical projects, working collaboratively with other teams to acquire and ingest new data sources. You will also work with the Principal Data Engineer, Data Architects, Database Administrators, Technical Architects, Solution Architects and Data Analytics team to set the enterprise data strategy and standards and agree implementation and governance.

Person specification

Main Responsibilities

• Managing data sources to improve data quality and conform them for analysis, developing processes to balance data availability, capacity and data archiving, while continually improving processes and efficiency in the acquisition and ingestion of data.
• Developing, maintaining and supporting data workflows, pipelines, ETL processes and end-to-end data solutions covering requirements review, data profiling and source system analysis, design, coding, testing, deployment and documentation of complex and large-scale data products, while working collaboratively with the analytics team to ensure the reliability, usability and integrity of critical datasets.
• Exercising key stakeholder management skills in order to manage expectations, listen and interpret business needs, communicate progress and facilitate difficult conversations, while building a ‘service culture’ around data.
• Keeping abreast of best practice in industry and government, ensuring data solutions comply with data privacy and information security requirements, working closely with relevant specialists.
• Managing the performance of suppliers and the data engineering team to improve capability, as well as creating the roadmap which balances immediate user needs with long-term investment, evaluation and selection of software products to build data engineering capability, contributing to the re-platforming of data analytics systems and the refresh of tooling.
• Line management, coaching and professional development of the team, where required.

Working Pattern 

Due to the business requirements of this role, it is only available on a full-time basis. However, compressed hours are available. 

Essential Skills

• Effectively leading and managing teams, leading and delivering technical products and projects in data analysis, solution design and end user reporting.
• Translating natural-language data quality rules into automated, testable and documented pipeline logic, applying modern programming languages and data analysis techniques (particularly Python and related libraries, regex and NLP), alongside qualitative and quantitative analysis, API integration, and JSON/CSV manipulation.
• Advising and leading the use of best practice IT programming and automation techniques and tools e.g. Git, Github, CI/CD pipelines & Python based automation.
• Leading the use of Cloud Data technologies, solutions and future Cloud Data Strategies g. AWS, EC2, VPC, RDS, IAM, R53, Lambda, Cloudwatch, AD & Docker.
• Working with stakeholders to gather requirements and deliver findings, presenting complex ideas and recommendations that inform decisions in a clear way to technical and non-technical audiences and senior customers.
• Using tools such as industry standard ETL tools, network databases and scheduling and orchestration tools g. SQL, Linux, bash scripts, PostgreSQL, Apache Derby, AWS Glue & Step Functions.
• Familiarity with data visualisation tools (e.g. Power BI), and emerging tools such as LLMs.
• Data engineering in the context of AI, Machine Learning, or automation-enabled products or services.