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

Apply Now

Head of Estates Data Engineering

Department for Work and Pensions (DWP)
Sheffield
2 days ago
Create job alert

The Estates Data, Systems & Reporting (DSR) teams mission is to serve as an agile enabler and assurer to DWP Estates in delivering its strategy through the whole data lifecycle for reliable, validated, and assured data, systems and insight. The role focuses on data and reporting assurance, optimisation, systemisation and collaboration across DWP Digital, Estates, Integrator and Supply Chain. It supports the delivery of the key enablers from the Estates Data Strategy: Data, Reporting, Infrastructure and Assurance, while also supporting Data Management, governance, data culture change, automation and systems assurance to enable the strategy.


Responsibilities

  • Communication – assess and interpret the needs of technical and non‑technical stakeholders, build effective requirements specifications, manage communication and expectations throughout project lifecycles, and engage senior stakeholders to ensure their requirements are understood and met. Develop an analytical community of practice, establish champions and enhance Estates governance, standards and processes.
  • Programming and build – design, write and iterate code from prototype to production‑ready, understanding security, accessibility and version control, and develop self‑generating documentation for Data Scientists and Analysts.
  • Technical understanding – apply the required breadth and depth of knowledge of specific technologies that underpin the role.
  • Testing – plan, design, manage, execute and report tests, using appropriate tools and techniques, while ensuring deployment risks are understood and documented.
  • Problem resolution – log, analyse and manage problems to identify and implement appropriate solutions.
  • Data integration – explore and ingest relevant data sources from WPS and other unexplored sources, focusing on Integrator DWH, Building Management Systems (BMS), sensor technologies (IoT) and other Big Data sources to improve decisions on building occupancy and related focus areas. Ingest a wide range of data assets from the Estates supply chain and publish within the Estates ecosystem.
  • Assurance – review internal / external Data Warehouses, models and reporting solutions for reliability and validity, assessing the data ecosystem lifecycle provisioning, transformation and representation to improve quality across platforms and organisations.
  • Data ecosystem – work with Digital Architects to scope, design and build a data ecosystem that effectively integrates Estates external data, uses Master Data Management tooling, and disseminates curated assets to appropriate functions.
  • Data analysis and synthesis – collaborate with DWP Digital, Estates and wider DWP analytical functions to embed and continuously improve Estates data capabilities, enabling analysts to develop insights that inform decisions.

Qualifications & Experience

  • Experience in designing, building, and deploying efficient, scalable, automated ETL/ELT pipelines (e.g., traditional data warehousing, modern cloud data warehousing, data lake/big data approaches).
  • Experience in designing and developing data solutions on public cloud (AWS/Azure/GCP).
  • Experience in one or more programming languages (SQL, Python).
  • Experience with data visualisation and analysis (e.g., PowerBI, SAS).
  • Experience in data storage and database technologies (e.g., RDBMS, NoSQL, distributed storage).
  • Experience with distributed version control tools and awareness of modern deployment methods (CI/CD).
  • Experience supporting the design of data models and data flows.
  • Experience in technical leadership, advising on architecture and technology, setting direction, collaborating across teams and mentoring junior staff.
  • Experience at all levels of customer relationship management and stakeholder liaison.
  • Experience working in real estates/property environment, with deep understanding of real estate data and analytics.
  • Influential in leading key stakeholders toward solutions that balance optimal commercial performance with strategy delivery.
  • Serve as a data champion, advocating data culture change, improving data literacy within the organisation.

Desirable Skills, Knowledge & Experience

  • Experience working with JIRA (or Azure DevOps or similar tools) within an Agile/Scrum environment.
  • Experience/understanding of software and data lifecycle management.
  • Education to degree level (not essential, experience is key); a relevant numerate, technical or computer science discipline would be an advantage.
  • Experience working in central government, either directly employed or as contractor.

Nationality Requirements

  • UK nationals
  • Nationals of the Republic of Ireland
  • Nationals of Commonwealth countries who have the right to work in the UK
  • Nationals of the EU, Switzerland, Norway, Iceland or Liechtenstein and family members of those nationalities with settled or pre‑settled status under the European Union Settlement Scheme (EUSS)
  • Nationals of the EU, Switzerland, Norway, Iceland or Liechtenstein and family members of those nationalities who have made a valid application for settled or pre‑settled status under the EUSS
  • Individuals with limited leave to remain or indefinite leave to remain who were eligible to apply for EUSS on or before 31 December 2020
  • Turkish nationals and certain family members of Turkish nationals who have accrued the right to work in the Civil Service

Applicants' Process

All candidates who are successful at the sift stage will undertake a single virtual video interview. You will be assessed against the experiences listed in the essential criteria and asked additional technical questions. Interviews are scheduled virtually; dates are subject to change.


Salary and Benefits

Alongside your salary of £75,026, Department for Work and Pensions contributes £21,735 towards your membership of the Civil Service Defined Benefit Pension scheme. Find out what benefits a Civil Service Pension provides.


DWP offers a broad benefits package focused on work‑life balance:



  • Working patterns that support balance such as job sharing, term‑time working, flexi‑time and compressed hours.
  • Generous annual leave: at least 23 days on entry, increasing up to 30 days over time (prorated for part‑time staff) plus 9 days public and privilege leave.
  • Financial wellbeing support, including interest‑free season ticket loans, a cycle‑to‑work scheme and an employee discount scheme.
  • Health and wellbeing support, including our Employee Assistance Programme and membership of the HASSRA competition and benefits programme.
  • Family‑friendly policies such as enhanced maternity leave and shared parental leave pay after one year continuous service.
  • Funded learning and development supporting progress in your role and career, including industry‑recognised qualifications, coaching, mentoring and talent development programmes.
  • An inclusive and diverse environment with opportunities to join professional and interpersonal networks such as the Women’s Network, National Race Network, National Disability Network (THRIVE) and many more.

Disability and Equality

The Civil Service encourages applications from people with disabilities, veterans, those who have recently left prison or have an unspent conviction, and other under‑represented groups. The Civil Service embraces diversity, promotes equal opportunities and runs a Disability Confident Scheme. We provide reasonable adjustments – including wheelchair access at interview or language support – to facilitate your application and interview experience.


Integrity and Authenticity

All examples in your application must be truthful, factually accurate and taken directly from your own experience. Plagiarism, such as presenting the work or ideas of others as your own or copying content from external sources, may result in withdrawal of your application. Artificial Intelligence can support applications, but all statements must be honest and factual. Findings of plagiarism may lead to internal disciplinary action.



  • Presenting the work, ideas and experience of others as your own.
  • Copying content or answers from an online or published source that is not your own.


#J-18808-Ljbffr

Related Jobs

View all jobs

Client Data Analyst, Real Estate

Principal Data Scientist & Machine Learning Researcher

Head of Data Engineering

Head of Data Engineering

Head of Data Engineering

Head of Machine Learning - DTG Capital Markets

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.

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.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.