Senior Data Engineer

Working closely with Analytics Engineers, Data Scientists, Cloud Architects, and Product Leads, you will ensure high-throughput data integration, maintain data governance standards, and empower enterprise business intelligence across our client operations. This position balances hands-on pipeline engineering with architectural governance and mentorship., * Data Pipeline & ETL/ELT Engineering: Design, build, and maintain fault-tolerant batch and streaming data pipelines using modern orchestration tools (Apache Airflow, Prefect, or Dagster).

• Enterprise Data Warehousing: Architect and optimize scalable data modeling schemas (Kimball methodology, star/snowflake schemas) across cloud data warehouses such as Snowflake, Databricks, or Google BigQuery.
• Data Quality, Observability & Governance: Implement automated testing, validation frameworks (dbt, Great Expectations), and data lineage tracking to guarantee data integrity, security, and compliance with UK GDPR and ISO 27001 standards.
• Distributed Processing & Integration: Write efficient code to process large-scale structured and unstructured datasets using Apache Spark (PySpark/Scala), SQL, and Python.
• DataOps & CI/CD Collaboration: Integrate data workflows into automated CI/CD pipelines (GitHub Actions, Azure DevOps) leveraging Infrastructure as Code (Terraform) for reproducible environments.
• Technical Leadership & Mentorship: Establish best practice guidelines for software engineering in data, maintain system documentation, and mentor mid-level and junior data engineers.

• 5+ years of commercial experience as a Data Engineer, Analytics Engineer, or Big Data Engineer delivering production-grade data pipelines.
• Expert-level proficiency in SQL and advanced data modeling strategies for modern cloud data platforms (Snowflake, Databricks, BigQuery, or AWS Redshift).
• Strong programming skills in Python or Scala for complex data processing.
• Proven track record with dbt (data build tool) for data transformation and modeling.
• Hands-on experience with workflow orchestration platforms (Apache Airflow, Astronomer, or Prefect).
• Proficiency in public cloud data ecosystems (AWS, Microsoft Azure, or GCP).
• Solid background in software development best practices: Git version control, unit testing, CI/CD, and peer code reviews.

Desirable

• Active Professional Certifications: Databricks Certified Data Engineer Professional, Snowflake Certified Advanced, or AWS Certified Data Analytics.
• Experience with real-time streaming engines (Apache Kafka, AWS Kinesis, or Spark Streaming).
• Understanding of Infrastructure as Code (IaC) using Terraform.
• Degree in Computer Science, Data Science, Software Engineering, Mathematics, or a related quantitative field.

Pulled from the full job description

• Annual leave
• Gym membership
• Free parking
• Company pension
• Cycle to work scheme
• Canteen
• On-site parking, * Annual performance-based bonus
• Hybrid working model (3 days central London office / 2 days remote)
• 25 days annual leave plus UK bank holidays
• Enhanced pension scheme (up to 8% company match)
• Private medical and dental cover
• Life assurance (4x base salary)
• £1,500 annual personal learning and professional development budget
• Fully paid professional certifications, examination fees, and conference passes
• Cycle to Work scheme & Electric Vehicle (EV) salary sacrifice scheme
• Enhanced maternity, paternity, and adoption leave
• Regular company socials, data hackathons, and team events