Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Data Engineer

TPXImpact Holdings Plc
London
1 day ago
Create job alert

About The Role

Job level: 10
Were looking for a Lead Data Engineer to join our Data Engineering and Analytics practice.
In this role, you will:
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.

Responsibilities

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.

Dimensions

Headcount

: Typically leads a multidisciplinary team or multiple workstreams (team size 515)

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 (612 months), ensuring that near-term work supports broader programme and client objectives.

About You

Professional knowledge and experience

Essential
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 wareho

using 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

Desirable
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)

Skills

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
Data Engineering and Manipulation
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
Testing (Data)
Review requirements and specifications, and define system integration testing conditions for complex data products and support others to do the same
Identify and manage issues and risks associated with complex data products and support others to do the same
Analyse and report system test activities and results for complex data products and support others to do the same
Other Skills
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.
Behaviours and PACT values

Purpose:

Be values-driven, recognising that our client's needs are paramount. Approach client engagements with professionalism and creativity, balancing commercial and operational needs.
Accountability:

Be accountable for delivering your part of a project on time and under budget and working well with other leaders.

Lead by example, promoting a culture where quality and client experience are foremost.
Craft:

B

alance multiple priorities while leading high-performing teams. Navigate ambiguity and set the technical direction and approach to support positive outcomes.
Togetherness:

Collaborate effectively with others across TPXimpact. Build strong relationships with colleagues and clients.
About Us

People-Powered Transformation

We're a purpose driven organisation, supporting organisations to build a better future for people, places and the planet. Combining vast experience in the public, private and third sectors and expertise in human-centred design, data, experience and technology, were creating sustainable solutions ready for an ever-evolving world.

At the heart of TPXimpact, were collaborative and empathetic. Were 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. Thats 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.
Benefits Include:
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.

Were an inclusive employer, and we care about diversity in our teams. Let us know in your application if you have accessibility requirements during the interview.

TPBN1_UKTJ

Related Jobs

View all jobs

Lead Data Engineer

Lead Data engineer

Lead Data Engineer - Microsoft Fabric - Hybrid - £75k

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.