Data Engineer – Build Scalable ETL Pipelines

About the role

Methods Analytics is looking for a Data Engineer to join our analytics team on a permanent basis. The role is primarily remote, with occasional travel to client sites and our offices in London, Sheffield and Bristol.

Key responsibilities

• Collaborate with cross‑functional teams to translate technical concepts for non‑technical audiences.
• Design, develop and maintain efficient ETL/ELT pipelines using Python, SQL and Apache Airflow.
• Build scalable data solutions on cloud platforms, leveraging Azure services.
• Develop and optimise data models using dimensional modelling techniques.
• Implement data‑governance, security and compliance best practices.
• Ensure data quality through rigorous QA and test‑driven development.
• Create intuitive dashboards for stakeholders.
• Monitor and tune performance of data systems.

Required profile

• Strong proficiency in SQL and Python for complex data problems.
• Hands‑on experience with Apache Spark (PySpark or Spark SQL).
• Experience building and optimising ETL/ELT pipelines.
• Familiarity with the Azure data stack and workflow orchestration tools such as Apache Airflow.
• Knowledge of containerisation (Docker) and CI/CD pipelines.
• Ability to design dimensional data models.
• Excellent communication skills for translating technical concepts to business audiences.

Required skills

• SQL
• Python
• Apache Spark (PySpark, Spark SQL)
• Azure (data services)
• Apache Airflow
• Docker
• Dimensional modelling
• CI/CD pipelines
• Test‑driven development
• Power BI
• Apache Superset
• AWS
• Google Cloud Platform
• Oracle
• Databricks
• Microsoft Fabric
• SSIS

What we offer

• Competitive salary range £40k‑£60k.
• Flexible remote‑first working model.
• Opportunities to work on innovative data projects across multiple industries.
• Professional development and community of practice within the engineering team.