Data & AI Infrastructure
Lead Data Engineer
Lead the technical design, build, and governance of scalable, enterprise-grade data platforms and analytics infrastructure for client engagements.
Salford, Greater Manchester / Hybrid
Full-time (37.5 hours/week)
Data & AI Infrastructure
Key responsibilities
- Architect serverless ELT/ETL data pipelines leveraging AWS cloud services, Snowflake, and modern lakehouse patterns (e.g., Databricks/PySpark).
- Design and maintain modular orchestration pipelines using dbt, Python, and workflow engines like Apache Airflow or Prefect.
- Build high-throughput event-driven ingestion pipelines (AWS SNS/SQS, Snowpipe, Kafka) and real-time streaming architectures.
- Establish data governance frameworks, including Medallion Architecture standards (Raw to Marts), Row-Level Security (RLS), and Data Quality contracts.
- Drive FinOps practices across client infrastructure to optimize data warehouse compute expenditure and query latency.
- Lead technical design reviews, establish GitOps CI/CD pipelines, and mentor cross-functional engineering teams.
Requirements
- 5+ years of commercial data engineering experience with proven leadership capability.
- Deep technical mastery of Python, Advanced SQL, dbt, and cloud data warehouses (Snowflake, BigQuery, or Redshift).
- Hands-on expertise with AWS cloud infrastructure (AWS CDK, S3, Lambda, IAM).
- Strong understanding of modern data modeling practices (Star Schema, Data Vault) and CI/CD automation.
- AWS or equivalent cloud certification preferred.