Senior Data Engineer

Alexander Associates
London, UK
1 day ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

Automation of Tests Microsoft Azure Big Data Cloud Storage Computer Programming Databases Data Architecture Information Engineering Data Governance Data Integration Extract Transform Load (ETL) Data Warehousing
+16 more
Python (Programming Language) SQL Azure NoSQL Performance Tuning Query Optimization SQL Databases Data Processing Cloud Platform System Azure Data Factory Apache Spark Git Pyspark Git Flow Software Version Control Data Pipelines Databricks

Requirements

  • 10+ years’ experience in Data Engineering, with a minimum of 3 years of hands-on Azure Databricks experience delivering production-grade solutions.
  • Strong programming proficiency in Python and Spark (PySpark) or Scala, with the ability to build scalable and efficient data processing applications.
  • Advanced understanding of data warehousing concepts, including dimensional modelling, ETL/ELT patterns, and modern data integration architectures.
  • Extensive experience working with Azure data services, particularly Azure Data Factory, Azure Blob Storage, Azure SQL Database, and related components within the Azure ecosystem.
  • Demonstrable experience designing, developing, and maintaining large-scale datasets and complex data pipelines in cloud environments.
  • Proven capability in data architecture design, including the development and optimisation of end-to-end data pipelines for performance, reliability, and scalability.
  • Expert-level knowledge of Databricks, including hands-on implementation, cluster management, performance tuning, and (ideally) relevant Databricks certifications.
  • Hands-on experience with SQL and NoSQL database technologies, with strong query optimisation skills.
  • Solid understanding of data quality frameworks, data governance practices, and implementing automated testing/validation within pipelines.
  • Proficient with version control systems such as Git, including branching strategies and CI/CD integration.
  • Experience working within Agile delivery environments, collaborating closely with cross-functional teams to deliver iterative, high-quality solutions.

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Good distractions

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