Senior Data Engineer

Phoenix
Edinburgh, United Kingdom
4 months ago
Applications closed

Related Jobs

View all jobs
Spotlight

Machine Learning Engineer - National Security (Gloucestershire)

Mind Foundry Gloucester, Gloucestershire, United Kingdom
On-site Clearance Required

Senior Data Engineer

Synthesia London, United Kingdom
Hybrid

Senior Data Engineer, Core Experimentation

OpenAI United Kingdom
£293,000 – £325,000 pa Hybrid

Data Scientist

Guidant Global London, United Kingdom
£600 – £850 pd On-site Clearance Required

Senior Simulation Data Engineer

PhysicsX London, United Kingdom

Senior Data Scientist

Adria Solutions Manchester, United Kingdom
Permanent

Senior Research Engineer - Data

Synthesia London, United Kingdom
Remote
Posted
19 Jan 2026 (4 months ago)
Senior Data Engineer

We have an incredible opportunity to join us here at Phoenix Group as a Senior Data Engineer to join our Engineering & Delivery team within Group IT.


Job Type: Permanent – Specialist Band 2


Location: This role could be based in our Birmingham, Telford or Edinburgh offices with a mix of office and remote work.


Flexible working: All our roles are open to part‑time, job‑share and other types of flexibility. We will discuss what is important to you during the recruitment process.


Closing date: 19/01/2026


Salary and benefits: £45,000 – £60,000 plus 16% bonus up to 32%, private medical cover, 38 days annual leave, excellent pension, 12× salary life assurance, career breaks, income protection, 3× volunteering days and more.


Job Description

We are seeking a Senior Data Engineer to join the Engineering and Delivery function in Group IT. This is a pivotal role for candidates with a strong background in data and engineering who want to shape how data drives every aspect of a modern pensions business. From operational efficiency and digital transformation to regulatory compliance and customer engagement, your work will influence decisions and enable change across the organisation.


As a Senior Data Engineer, you will be responsible for designing, implementing and optimizing data solutions on cloud platforms, with a strong emphasis on Databricks. Beyond analytics, you will help embed data capabilities into core business processes, supporting areas such as operations, digital services, risk management, accounting and actuarial. You will collaborate with cross‑functional teams—including data scientists, analysts, product owners and operational leaders—to ensure data is a trusted, integrated asset powering innovation and business outcomes.


Key Responsibilities

  • Design and implement end‑to‑end data engineering solutions across multiple platforms, including Azure, Databricks, SQL Server and Salesforce, enabling seamless data integration and interoperability.
  • Architect and optimise Delta Lake environments within Databricks to support scalable, reliable and high‑performance data pipelines for both batch and streaming workloads.
  • Develop and manage robust data pipelines for operational, analytical and digital use cases, leveraging best practices for data ingestion, transformation and delivery.
  • Integrate diverse data sources—cloud, on‑premises and third‑party systems—using connectors, APIs and ETL frameworks to ensure consistent and accurate data flow across the enterprise.
  • Implement advanced data storage and retrieval strategies that support operational data stores (ODS), transactional systems and analytical platforms.
  • Collaborate with cross‑functional teams (data scientists, analysts, product owners and operational leaders) to embed data capabilities into business processes and digital services.
  • Optimize workflows for performance and scalability, addressing bottlenecks and ensuring efficient processing of large‑scale datasets.
  • Apply security and compliance best practices, safeguarding sensitive data and ensuring adherence to governance and regulatory standards.
  • Create and maintain comprehensive documentation for data architecture, pipelines and integration processes to support transparency and knowledge sharing.

Qualifications

  • Proven experience in enterprise‑scale data engineering, with a strong focus on cloud platforms (Azure preferred) and cross‑platform integration (e.g., Azure ↔ Salesforce, SQL Server).
  • Deep expertise in Databricks and Delta Lake architecture, including designing and optimising data pipelines for batch and streaming workloads.
  • Strong proficiency in building and managing data pipelines using modern ETL/ELT frameworks and connectors for diverse data sources.
  • Hands‑on experience with operational and analytical data solutions, including ODS, data warehousing and real‑time processing.
  • Solid programming skills in Python, Scala and SQL, with experience in performance tuning and workflow optimisation.
  • Experience with cloud‑native services (Azure Data Factory, Synapse, Event Hub, etc.) and integration patterns for hybrid environments.

We Want To Hire The Whole Version Of You

We are committed to ensuring that everyone feels accepted and welcome; applicants from all backgrounds are encouraged to apply. If your experience looks different from what we’ve advertised and you believe you can bring value to the role, we would love to hear from you.


If you require any adjustments to the recruitment process, please let us know so we can help you to be at your best.


Please note that we reserve the right to remove adverts earlier than the advertised closing date. We encourage you to apply at the earliest opportunity.


Find out more about:



  • Guide for Candidates: thephoenixgroup.pagetiger.com/guideforcandidates
  • Find or get answers from our colleagues: www.thephoenixgroup.com/careers/talk-to-us


#J-18808-Ljbffr

Industry Insights

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

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Where to advertise machine learning jobs UK in 2026: the specialist boards and communities that reach ML, MLOps and deep learning engineering talent. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Machine Learning Jobs UK 2026: What to Expect Over the Next 3 Years

Machine Learning Jobs UK 2026: roles, salaries and the MLOps, LLM and generative AI hiring trends shaping UK ML careers over the next three years. Machine learning has undergone a transformation that few technology disciplines can match. In the space of three years it has moved from a specialism sitting at the edges of most organisations' technology strategies to a capability that sits at the centre of them. The tools have changed, the expectations have shifted, and the range of industries treating machine learning as a core business function — rather than an experimental one — has expanded dramatically. For job seekers, this creates both opportunity and complexity in roughly equal measure. The machine learning jobs market of 2026 is significantly larger than it was three years ago, but it is also significantly more demanding. Employers have developed more sophisticated expectations, the technical bar for specialist roles has risen, and the landscape of tools, frameworks, and architectural patterns that practitioners are expected to know has broadened considerably. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which specialisms are attracting the most investment, which technologies are reshaping what machine learning engineers and researchers are expected to build, and how the definition of a machine learning career is evolving beyond the model-building core toward a much wider range of roles across the full ML lifecycle. This article breaks down what the UK machine learning jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.