At a Glance
- Tasks: Build scalable data pipelines and automate workflows using AWS, Databricks, and PySpark.
- Company: Join a high-impact engineering team in a collaborative environment.
- Benefits: Competitive salary of £80k-£95k, hybrid work model, and career growth opportunities.
- Other info: Start in August and enjoy a dynamic workplace in London or Glasgow.
- Why this job: Work with cutting-edge technology and make a real impact on marketing insights.
- Qualifications: Experience in cloud environments, AWS services, and strong skills in PySpark and SQL.
The predicted salary is between 80000 - 90000 £ per year.
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.
Remote Senior Data Engineer - AWS/Databricks/PySpark - August Start Date in Bristol employer: WüNDER_TALENT
Join a dynamic and innovative team as a Senior Data Engineer, where you'll have the opportunity to work on cutting-edge data solutions in a hybrid environment that balances flexibility with collaboration. With a strong focus on employee growth, our company offers extensive training and development opportunities, alongside a supportive work culture that values creativity and teamwork. Located in vibrant Central London or Glasgow, you will enjoy the unique advantages of these cities while contributing to impactful projects that drive real business insights.
