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

WüNDER TALENT
Woking, United Kingdom
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
£ 90K

Job location

Woking, United Kingdom

Tech stack

Airflow
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Continuous Integration
Data Cleansing
Data Governance
ETL
Data Security
Data Systems
DevOps
Github
Standard Sql
Software Engineering
T-SQL
Unstructured Data
Scripting (Bash/Python/Go/Ruby)
Cloud Platform System
Spark
GIT
Data Lake
PySpark
Infrastructure Automation Frameworks
Real Time Data
Terraform
Software Version Control
Data Pipelines
Databricks

Job description

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.

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