Remote Senior Data Engineer - AWS/Databricks/PySpark - August Start Date in Gloucester

You’ll be involved in designing and building production-grade ETL pipelines, driving DevOps practices across data systems and contributing to high-availability architectures using tools like Databricks, Spark and Airflow- all within a modern AWS ecosystem.

• Proven experience as a Data Engineer in cloud-first environments. \n

• Strong commercial knowledge of AWS services (e.g. S3, Glue, Redshift). \n

• Advanced PySpark and Databricks experience (Delta Lake, Unity Catalog, Databricks Jobs etc). \n

• Proficient in SQL (T-SQL/SparkSQL) and Python for data transformation and scripting. \n

• Hands-on experience with workflow orchestration tools such as Airflow. \n

• Strong version control and DevOps exposure (Git, GitHub Actions, Terraform). \n

• Familiar with data quality tools and metadata/cataloguing (e.g. Great Expectations, Unity Catalog). \n

• Beneficial: MarTech domain knowledge. \n

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• Architect and build scalable, secure data pipelines using AWS, Databricks and PySpark. \n

• Design and implement robust ETL/ELT solutions for both structured and unstructured data. \n

• Automate workflows and orchestrate jobs using Airflow and GitHub Actions. \n

• Integrate data with third-party APIs to support real-time marketing insights. \n

• Collaborate closely with cross-functional teams including Data Science, Software Engineering and Product. \n

• Champion best practices in data governance, observability and compliance. \n

• Contribute to CI/CD pipeline development and infrastructure automation (Terraform, AWS DevOps). \n

• Provide input into technical decisions, peer reviews and solution design. \n

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