Senior Data Engineer - AWS/Databricks/PySpark - August Start Date

Senior Data Engineer| AWS/Databricks/PySpark | London/Glasgow (Hybrid) | August Start

Role: Senior Data Engineer

Location: This is a hybrid engagement represented by 2 days/week onsite, either in Central London or Glasgow.

Start Date: Must be able to start mid-August.

Salary: £80k-£90k (Senior) | £90k-£95k (Lead)

About The Role

Our partner is looking for a Senior Data Engineer to join a high-impact engineering team delivering scalable data solutions for complex marketing and customer insight use cases. This is an opportunity to work on cutting-edge data pipelines, cloud-native platforms and real-time data flows in a collaborative, forward-thinking environment.

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.

Responsibilities

• Architect and build scalable, secure data pipelines using AWS, Databricks and PySpark.
• Design and implement robust ETL/ELT solutions for both structured and unstructured data.
• Automate workflows and orchestrate jobs using Airflow and GitHub Actions.
• Integrate data with third-party APIs to support real-time marketing insights.
• Collaborate closely with cross-functional teams including Data Science, Software Engineering and Product.
• Champion best practices in data governance, observability and compliance.
• Contribute to CI/CD pipeline development and infrastructure automation (Terraform, AWS DevOps).
• Provide input into technical decisions, peer reviews and solution design.

Requirements

• Proven experience as a Data Engineer in cloud-first environments.
• Strong commercial knowledge of AWS services (e.g. S3, Glue, Redshift).
• Advanced PySpark and Databricks experience (Delta Lake, Unity Catalog, Databricks Jobs etc).
• Proficient in SQL (T-SQL/SparkSQL) and Python for data transformation and scripting.
• Hands-on experience with workflow orchestration tools such as Airflow.
• Strong version control and DevOps exposure (Git, GitHub Actions, Terraform).
• Familiar with data quality tools and metadata/cataloguing (e.g. Great Expectations, Unity Catalog).
• Beneficial: MarTech domain knowledge.

Notable: This is a hybrid engagement represented by 2 days/week onsite, either in Central London or Glasgow. You must be able to start in August.

Senior Data Engineer| AWS/Databricks/PySpark | London/Glasgow (Hybrid) | August Start