Data Engineer

Cognizant
London, UK
17 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Data Analysis Microsoft Azure Big Data Cloud Storage Information Engineering Data Governance Extract Transform Load (ETL) Data Transformation DevOps Logic Synthesis of Circuits Python (Programming Language) Azure Data Lake
+16 more
SQL Databases Azure Data Factory Apache Spark Git SC Clearance Microsoft Fabric Data Lakes Pyspark Infrastructure Automation Frameworks Information Technology Data Lakehouse Azure Synapse Analytics Software Version Control Data Pipelines Legacy Systems Databricks

Job description

  • This is a pivotal engineering role at the heart of one of the most significant data transformation programmes in UK government. You will be joining a strategic engagement programme to design, build, and operationalise a cloud-native data lakehouse on Microsoft Azure Fabric.
  • This is with the UK’s largest public service department, serving over 22 million citizens, and this platform will directly underpin data-driven decision-making at national scale.
  • You will take a leading role in the design and delivery of data pipelines, data transformation layers, and lakehouse infrastructure using Microsoft Fabric, Azure Data Factory, and related Azure-native technologies.
  • You will work in agile squads alongside architects, analysts, and DevOps engineers, contributing to private beta builds, public beta expansion, and full platform operationalisation., * Design, build, and optimise data pipelines using Microsoft Fabric (Data Factory, Dataflows Gen2) and Azure Data Factory to ingest data from legacy systems and third-party sources.
  • Develop and maintain the Bronze, Silver, and Gold layers of the lakehouse architecture using OneLake, Delta Lake, and Apache Spark within Fabric.
  • Implement data transformation logic using PySpark, SQL, and Fabric Notebooks; ensure data quality, lineage, and cataloguing via Microsoft Purview.
  • Collaborate with Technical Architects and Infrastructure Engineers to support CI/CD pipelines, infrastructure-as-code, and platform automation
  • Contribute to knowledge transfer workshops, running instructions, and documentation to build internal capability.
  • Support governance compliance including Digital Design Authority reviews, Red Lines Assessments, and security controls.

Requirements

  • Strong experience with Microsoft Azure Fabric (Lakehouses, Data Pipelines, Dataflows Gen2, Fabric Notebooks)
  • Strong experience with Azure Data Factory (ADF) for orchestration and data movement
  • Strong proficiency in PySpark, SQL, and Python for large-scale data transformation
  • Strong experience with Delta Lake, Apache Spark, and OneLake architecture
  • Good knowledge of Microsoft Purview for data governance, cataloguing, and lineage
  • Good experience with Azure DevOps, Git-based version control, and CI/CD pipelines
  • Good understanding of data lakehouse architecture (medallion architecture - Bronze/Silver/Gold)
  • Good knowledge of Azure storage services (ADLS Gen2, Azure Blob Storage

Nice to have skills

  • Experience with Azure Synapse Analytics or migration from Synapse to Fabric
  • Familiarity with Databricks or equivalent distributed processing platforms
  • Experience in UK public sector or government data environments
  • Understanding of SC clearance requirements and government security classifications
  • Knowledge of DDAT frameworks and GDS delivery standards, * Relevant degree in Computer Science, Data Engineering, or related discipline (or equivalent experience)
  • Microsoft Certified: Azure Data Engineer Associate (DP-203) - desirable
  • Microsoft Fabric Analytics Engineer (DP-600) - desirable

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on dejobs.org

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

2:17 min

Mapping the maturity roadmap for scaled devops adoption

Dominik Krichbaum Dominik Krichbaum · WWC Europe 2026

4:32 min

Harnessing Spark with Python using PySpark and Py4J

Ayon Roy · LIVE

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

56 sec

Favorite git commands and the importance of patch commits

Eileen Uchitelle Eileen Uchitelle +1 · Coffee With Developers

Videos

See all

Related articles

See all