Senior Data Engineer – Cloud Lakehouse Platforms

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 also leading proof‑of‑concepts, pre‑sales activities, reusable frameworks, and reference architectures.

Key responsibilities

• Drive end‑to‑end data‑platform projects 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, observability and cost‑control mechanisms.
• Implement data‑governance controls (GDPR‑compliant PII handling, lineage, quality tests) using Unity Catalog, Purview or Fabric governance.
• 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 (star/snowflake, Data Vault, lakehouse).
• Hands‑on experience with Databricks, Microsoft Fabric or Snowflake, including performance tuning and cost optimisation.
• Proven track record building both batch and streaming pipelines.
• Strong Python and SQL skills, solid grasp of CI/CD and Infrastructure‑as‑Code (Terraform or CloudFormation).

Required skills

• Python
• PySpark
• SQL
• Databricks (Spark/Delta Live Tables)
• Microsoft Fabric
• Snowflake
• AWS, Azure, GCP
• dbt
• Airflow
• Kafka / Flink
• GitHub Actions / Azure DevOps
• Terraform / CloudFormation
• Great Expectations
• Monte Carlo
• Prometheus / Grafana
• Unity Catalog / Purview