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Senior Data Engineer

Sure Exec Search
united kingdom, united kingdom
2 months ago
Applications closed

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Senior Data Engineer

Data Integration Specialist / Performance Data Engineer

Location:London / Open to both Remote & Hybrid

Rate:£450 - £500 per day (Inside IR35)

Contract:5 months (potential to extend)


The Opportunity:

We're partnering with a globally recognised business to find aSenior Data Engineerwith a passion for data performance, cloud architecture, and scalable integration.


This role sits at the heart of operational performance, enabling data-driven decisions through robust data pipelines, smart modelling, and seamless integrations. You'll play a critical part in modernising and scaling the data estate across multiple cloud-native tools and platforms.


What You'll Be Doing:

  • Build and optimiseETL/ELT pipelinesacross structured and unstructured data sources usingAirbyte,Airflow,DBT Core, andAWS Glue
  • Design and maintaindimensional modelsinSnowflake, including SCDs and best practices for indexing, clustering, and performance
  • Collaborate cross-functionally with analysts and business teams to supportPower BIand enterprise-wide self-serve analytics
  • Implement best practices indata governance, including data quality checks, lineage tracking, and anomaly detection
  • Automate data orchestration using tools such asAirflow,Lambda, orStep Functions
  • Support financial and operational reporting through snapshot tables and audit-friendly data structures


What We're Looking For:

  • Strong understanding ofEnterprise Data Warehousing (EDW)with hands-on experience inKimball-style modelling
  • Expert-levelSQLskills for complex transformation and query tuning
  • Deep knowledge ofSnowflakeincluding optimisation, cost management, and architecture
  • Experience withmodern data stacks– especiallyDBT Core,Airbyte, andAirflow
  • Familiarity withAWS data services(e.g., S3, Lambda, Step Functions)
  • Proven ability to support scalable reporting frameworks and drive data reliability


Bonus Points For:

  • Experience withdata observabilityandCI/CDpipelines for data engineering
  • Exposure tostreaming platformslike Kafka or Kinesis
  • Comfort working in fast-moving, cross-functional environments
  • BI tool experience – Power BI, Tableau, or similar
National AI Awards 2025

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