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Methods Business and Digital Technology

Digital transformation for UK public sector

Data Engineer

Data EngineeringUpdated on Nov 10
Full-time

About the Job

Requirements

  • Ability to work iteratively with architects, process owners, finance, procurement, workforce, and operational stakeholders to turn ambiguous business issues into clear data analysis, engineering actions, and controlled tactical fixes.
  • Understanding of data ownership, stewardship, lineage, metadata, controls, and data quality monitoring, and ability to produce reusable documentation for an enduring data governance model.
  • Experience implementing and advocating test-driven development methodologies in data pipeline workflows, including unit testing, integration testing, and data quality validation frameworks.
  • Proven experience leading technical aspects of data projects.
  • Strong data architecture and modelling skills, including designing scalable data solutions.
  • Deep understanding of data warehouse design principles and methodologies.
  • Advanced knowledge of optimisation techniques for large-scale data processing.
  • Strong proficiency in SQL and Python for complex data problems.
  • Hands-on experience with Apache Spark, including PySpark or Spark SQL.
  • Experience with the Azure data stack.
  • Knowledge of workflow orchestration tools such as Azure Data Factory or Apache Airflow.
  • Experience with containerisation technologies such as Docker.
  • Proficiency in dimensional modelling techniques.
  • Experience with CI/CD pipelines for data solutions.
  • Strong communication skills for translating complex technical concepts.
  • UK Security Check (SC) clearance is required, either already held or with willingness to undergo the process; candidates must complete Baseline Personnel Security Standard onboarding checks.

Responsibilities

  • Design, build, and improve ETL and ELT pipelines for data ingestion, profiling, reconciliation, cleansing, and reporting across enterprise source systems.
  • Build data catalogues, data flows, interface views, and trusted source views.
  • Design and architect modern data solutions aligned with business objectives and technical requirements, supporting current-state and target-state data architecture.
  • Help clients improve confidence in operational, workforce, procurement, and financial reporting through timely, accurate, and reconcilable data.
  • Build scalable and performant data solutions using cloud platforms and open-source software.
  • Develop data models for enterprise-level analytical needs.
  • Optimise large-scale data processing systems for performance and cost-efficiency.
  • Implement data quality frameworks and monitoring solutions.
  • Evaluate new technologies to enhance data engineering capabilities.
  • Collaborate with stakeholders to translate business requirements into technical specifications.
  • Present technical solutions to leadership and non-technical stakeholders.
  • Contribute to the Methods Analytics Engineering Practice through participation in its internal community of practice.
  • Enable business leaders to make informed decisions through timely, accurate data insights.
  • Establish reusable engineering standards, patterns, and documentation that support quality, maintainability, and repeatable Data Foundations delivery.
  • Drive adoption of modern data architectures and platforms.
  • Deliver data solutions that enhance user experience.
  • Elevate the technical capabilities of the data engineering team.
  • Help cultivate a data-driven culture within the organisation.
  • Establish technical standards and patterns that ensure quality and maintainability.

Desired Qualifications

  • Experience designing and implementing data mesh or data fabric architectures.
  • Knowledge of cost optimisation strategies for cloud data platforms.
  • Experience with data quality frameworks and implementation.
  • Experience with data visualisation tools such as Power BI or Apache Superset.
  • Experience with other cloud data platforms such as AWS, GCP, or Oracle.
  • Experience with modern unified data platforms such as Databricks or Microsoft Fabric.
  • Experience with Kubernetes for container orchestration.
  • Understanding of streaming technologies such as Apache Kafka and event-based architectures.
  • Experience with high-performance, large-scale data systems.
  • Willingness to obtain Developed Vetting (DV) clearance where required for some roles or projects.

About the Company

Methods Business and Digital Technology

Digital transformation for UK public sector

Methods Business and Digital Technology helps UK public sector organisations upgrade their services with digital transformation. It partners with central government departments and agencies to move from old, siloed legacy infrastructure to a platform-based operating model, keeping costs low while improving front-end public services for citizens. The company provides specialist skills and deep public-sector expertise to transform operations, reduce reliance on expensive suppliers, and strengthen control over customer relationships and operating models. Its goal is to safeguard public-facing services, apply digital thinking to keep services citizen-centered, and deliver real savings and benefits for government and society.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
1990

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