Data Engineer – Analytics & Platform (All Levels)

About the role

We are seeking Data Engineers of all experience levels to join our UK‑wide team. The role involves building and operating the core data infrastructure that powers analytics, business intelligence, data science and machine‑learning initiatives. You will work on end‑to‑end data pipelines, from ingestion through modelling, transformation and observability.

Key responsibilities

• Design, develop and maintain production ELT/ETL pipelines that meet business volume and latency requirements.
• Model data in warehouses or lakehouses using dimensional, Data Vault, One‑Big‑Table or domain‑driven approaches.
• Build and manage transformation layers with dbt (or equivalent), ensuring testing, documentation and lineage.
• Operate orchestration tools such as Airflow, Dagster or Prefect and manage associated workflows.
• Administer cloud data warehouses and lakehouses (Snowflake, BigQuery, Redshift, Synapse, Databricks).
• Implement data quality, testing, monitoring and observability across pipelines and models.
• Create streaming pipelines where needed using Kafka, Kinesis, Pub/Sub or Flink.
• Collaborate with analysts, data scientists, BI developers and ML engineers to deliver required data products.
• Contribute to data governance, cataloguing, access management and platform security.

Required profile

• Strong software engineering discipline combined with a genuine interest in data modelling.
• Ability to make pragmatic decisions about building versus buying solutions.
• Experience mentoring junior engineers and leading platform strategy for senior‑level candidates.

Required skills

• Advanced SQL (complex transformations, performance tuning, warehouse‑specific dialects).
• Python (or Scala/Java where relevant) for pipeline development.
• Hands‑on experience with dbt or similar transformation tools.
• Orchestration experience (Airflow, Dagster, Prefect).
• Knowledge of cloud data warehouses/lakehouses (Snowflake, BigQuery, Redshift, Synapse, Databricks).
• Familiarity with streaming technologies (Kafka, Kinesis, Pub/Sub, Flink).