Responsibilities

• Lead the design, development, management and optimisation of data pipelines to ensure efficient data flows, recognising and sharing opportunities to reuse data flows where possible.
• Coordinate teams and set best practices and standards when it comes to data engineering principles.
• Champion data engineering across projects and clients. Lead by example, holding responsibilities for team culture, and how projects deliver the most impact and value to our clients.
• Be accountable for the strategic direction, delivery and growth of our work.
• Lead teams, strands of work and outcomes, owning commercial responsibilities.
• Hold and manage uncertainty and ambiguity on behalf of clients and our teams.
• Ensure teams and projects are inclusive through how you lead and manage others.
• Effectively own and hold the story of our work, ensuring we measure progress against client goals and our DT missions.
• Work with our teams to influence and own how we deliver more value to clients, working with time and budget constraints.
• Strategically plan the overall project and apply methods and approaches.
• Demonstrably share work with wider audiences.
• Elevate ideas through how you write, speak and present.
• Work with data analysts, engineers and data science and AI specialists to design and deliver products into the organisation effectively.
• Understand the reasons for cleansing and preparing data before including it in data products and can put reusable processes and checks in place.
• Access and use a range of architectures (including cloud and on-premise) and data manipulation and transformation tools deployed within the organisation.
• Optimise data pipelines and queries for performance and cost efficiency in distributed environments.

Dimensions

• Headcount: Typically leads a multidisciplinary team or multiple workstreams (team size 5-15)
• Resource complexity: Provides leadership across multiple workstreams or technical domains within a project or programme. Responsible for delivery coordination, prioritisation, and quality, often overseeing more junior leads or specialists.
• Problem-solving responsibility: Solves highly complex problems, balancing technical, user, business, and operational needs. Applies expert judgement to make decisions, manage risks, and guide teams through ambiguity.
• Change management requirements: Leads or co-leads significant change initiatives. Responsible for managing stakeholder expectations, supporting adoption, and embedding sustainable ways of working.
• Internal/External interactions: Acts as a trusted partner to client and internal stakeholders at multiple levels. Leads workshops, presentations, and stakeholder engagement to ensure buy-in, alignment, and delivery clarity.
• Strategic timeframe working towards: Works across mid- to long-term delivery cycles (6-12 months), ensuring that near-term work supports broader programme and client objectives.
• Collaborates with data analysts, engineers and data science and AI specialists to design and deliver products into the organisation effectively.
• Understand the reasons for cleansing and preparing data before including it in data products and can put reusable processes and checks in place.
• Access and use a range of architectures (including cloud and on-premise) and data manipulation and transformation tools deployed within the organisation.
• Optimise data pipelines and queries for performance and cost efficiency in distributed environments

Qualifications and Expertise

• Proven experience in data engineering, data integration and data modelling
• Expertise with cloud platforms (e.g. AWS, Azure, GCP)
• Expertise with modern cloud data platforms (e.g. Microsoft Fabric, Databricks)
• Expertise with multiple data analytics tools (e.g. Power BI)
• Deep understanding of data warehousing concepts, ETL/ELT pipelines and dimensional modelling
• Proficiency in advanced programming languages (Python/PySpark, SQL)
• Experience in data pipeline orchestration (e.g. Airflow, Data Factory)
• Familiarity with DevOps and CI/CD practices (Git, Azure DevOps etc)
• Ability to communicate technical concepts to both technical and non-technical audiences
• Proven experience in delivery of complex projects in a fast paced environment with tight deadlines
• Advanced knowledge of data governance, data standards and best practices
• Experience in a consultancy environment, demonstrating flexibility and adaptability to client needs
• Experience defining and enforcing data engineering standards, patterns, and reusable frameworks
• Professional certifications in relevant technologies (e.g. Microsoft Azure Data Engineer, AWS Data Analytics, Databricks Certified Professional Data Engineer), Data Development Process
• Design, build and test data products that are complex or large scale
• Build and lead teams to complete data integration services integration and reusable pipelines that meet performance, quality and scalability standards
• Collaborate with architects to align solutions with enterprise data strategy and target architectures, Proficiency in developing and maintaining complex data models (conceptual, logical and physical).
• Strong skills in data governance and metadata management.
• Experience with data integration design and implementation.
• Ability to write efficient, maintainable code for large scale data systems.
• Experience with CI/CD pipelines, version control, and infrastructure-as-code (e.g. Git, Azure DevOps).
• Strong stakeholder communication skills, with the ability to translate technical concepts into business terms.
• Ability to mentor junior engineers, foster collaboration, and build a high-performing data engineering culture.

Benefits

• 30 days holiday + bank holidays
• 2 volunteer days for causes that you are passionate about
• Maternity/paternity - 6 months Maternity Leave, 3 months Paternity Leave
• Life assurance
• Employer pension contribution of 5%
• Health cash plan
• Personal learning and development budget
• Employee Assistance Programme
• Access to equity in the business through a Share Incentive Plan
• Green incentive programmes including Electric Vehicle Leasing and the Cycle to Work Scheme
• Financial advice
• Health assessments

About TPXimpact - Digital Transformation

We drive fundamental change in approaches to product and service development, delivery and technology. Our agile, multidisciplinary teams use technology, design and data to deliver better results, improving outcomes for individuals, organisations and communities. By working in the open, in partnership with our clients, we not only transform their systems and services but also build the capability of their teams, so work can continue without us in the longer term. Our focus is sustainable change, always delivered with positive impact.

We’re collaborative and empathetic. We’re a team of passionate people who care deeply about the work we do and the impact we have in the world. We know that change happens through people, with people and for people. That’s why we believe in people-powered transformation. Working in close collaboration with our clients, we seek to understand their unique challenges, questioning assumptions and building in their teams the capabilities and confidence to continue learning, iterating and adapting.