Senior Data Engineer

About the role

We’re expanding our Data Engineering practice and looking for a senior-level engineer who can design, automate, and scale modern lakehouse and warehouse platforms on Azure, AWS, or GCP. In this role you’ll partner with product managers, analysts, and data scientists to unlock governed, high‑quality data for batch and streaming use‑cases while leading internal initiatives such as proof‑of‑concepts and pre‑sales activities.

Key responsibilities

• Drive end‑to‑end data‑platform projects from requirement workshops to production hand‑over using Databricks, Microsoft Fabric, Snowflake and associated cloud services.
• Build and optimise ETL/ELT pipelines (batch, micro‑batch, real‑time) with Python/PySpark, dbt, Airflow, Kafka/Flink and cloud‑native tools.
• Automate deployment of data stacks via Git‑based CI/CD, implement observability and cost‑control measures.
• Implement data‑governance controls (GDPR‑compliant PII handling, lineage, quality tests) using Unity Catalog, Purview or Fabric’s governance layer.
• Mentor mid‑level engineers, codify best practices and contribute to architecture standards and run‑books.

Required profile

• 5+ years of data engineering experience, with at least 3 years in a cloud environment (AWS, Azure or GCP).
• Expert knowledge of data‑warehouse modelling concepts such as star/snowflake, Data Vault and lakehouse.
• Hands‑on experience with Databricks (Spark/Delta Live Tables), Microsoft Fabric or Snowflake, including performance tuning and cost optimisation.
• Proven track record building both batch and streaming pipelines.

Required skills

• Python, PySpark, SQL.
• Databricks, Microsoft Fabric, Snowflake.
• ETL/ELT tools: dbt, Airflow, Kafka, Flink.
• Git‑based CI/CD (GitHub Actions, Azure DevOps) and Infrastructure‑as‑Code (Terraform, CloudFormation).
• Data‑ops and observability tools: Great Expectations, Monte Carlo, Prometheus, Grafana.
• Data‑governance platforms: Unity Catalog, Purview.