Data Engineer

Positive Employment
Newbury
1 month ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Positive Employment is currently recruiting for a Data Engineer for our client a government organisation in West Berkshire.

The successful post holder will display strong system integration capabilities to ensure that data flows between systems are aligned, reliable, and continuously improved.

Responsibilities will include implementing platform enhancements, managing operational processes, and delivering system and database customisations—covering SQL Server, QTC/Unit4 environments, and system-to-system migration assessments. The post ensures that data remains trusted, secure, well-structured, and readily available to support analytics, reporting, and digital services.

This role is a temporary contract initially for 3 months with the possibility to extend. This role is hybrid working with 2 days per week in the office required.

Duties and Responsibilities but not limited to:

  • Build and maintain batch and streaming data pipelines
  • Implement reliability practices (observability, SLAs/SLOs, testing, data contracts).
  • Optimise storage and compute performance.
  • Deploy pipelines using CI/CD and IaC.
  • Deliver curated datasets and semantic layers for BI, analytics, and ML.
  • Support ML feature engineering and model delivery.
  • Define scalable data architecture patterns and integration designs (ingestion, storage, transformation, analytics).
  • Develop and maintain conceptual, logical, and physical data models.
  • Ensure secure, efficient, and compliant dataflows across SaaS, cloud, and on-prem systems.
  • Embed data governance foundations (quality, lineage, cataloguing, metadata, retention.
  • Identify and manage data-related risks, ensuring privacy-by-design and regulatory compliance.
  • Establish access controls, classification rules, and protective security measures.
  • Provide architectural guidance and review for pipelines, APIs, and system-to-system integrations.
  • Assess and recommend platforms, tools, and technologies that support scalability and strategic needs.

Personal Requirements:

  • 3–5+ years’ experience with Microsoft SQL Server (2016+) and SSIS in production environments.
  • Strong SQL Server engineering: advanced T-SQL, indexing, performance tuning, execution plans, statistics, partitioning, tempdb optimisation.
  • Proven experience with ETL/ELT development and design patterns (incremental loads, CDC, SCD, error handling, idempotency).
  • Strong data modelling skills (Kimball, dimensional, relational). [Data Engineer JD | Word].
  • Proficiency with SQL Server Agent, SSIS logging, SSISDB deployment, and orchestration workflows..
  • Knowledge of data governance, metadata, cataloguing, and lineage principles.
  • Experience with cloud data services (Azure SQL/Managed Instance, Azure Data Factory/Synapse Pipelines, modernising SSIS workloads to ADF/SSIS IR). (Desirable).
  • Automation and scripting skills (PowerShell or Python).
  • Experience supporting Power BI, semantic models, or SSAS Tabular (Desirable).
  • Familiarity with SQL monitoring and observability tools (Redgate, SentryOne, custom telemetry). (Desirable).
  • Experience with metadata management or data catalogue tools. (Desirable).

Working Hours: 37hrs / 9:00am - 17:00pm / Mon–Fri

Pay: £350.00 per day

Please note this role is within the scope of IR35.

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.

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

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. 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.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.