We are recruiting on behalf of our client for an experienced Senior Data Engineer with strong AWS expertise to design, build and deliver scalable, secure and resilient data solutions.
Our client works with organisations operating in complex, secure and highly regulated environments, with a significant focus on the public sector and defence.
This is a hands‑on senior engineering role, combining deep data engineering expertise with technical ownership, client engagement and the ability to guide other engineers and influence engineering practices.
The Role
As a Senior Data Engineer, you’ll take a leading role in designing and building modern data platforms, pipelines and services within AWS.
You’ll work closely with architects, engineers, security specialists and client teams to understand requirements and turn them into robust, maintainable and secure data solutions.
Alongside hands‑on engineering, you’ll help establish engineering standards and patterns, contribute to key technical decisions and support the development of other engineers within the team.
What You’ll Do
- Design, build and maintain scalable data platforms and data pipelines within AWS
- Develop robust ETL/ELT processes for ingesting, transforming and processing data from multiple sources
- Design and implement data solutions using AWS services such as S3, Glue, Lambda, Athena, Redshift, EMR and related technologies
- Design data models and storage approaches appropriate to analytical and operational requirements
- Develop solutions using Python, SQL and modern data engineering frameworks
- Apply infrastructure-as-code and automation approaches to the deployment and management of data platforms
- Build data quality, validation, monitoring and observability into engineering solutions
- Ensure security, governance and data protection requirements are considered throughout solution design and delivery
- Work with architects, cloud engineers, security specialists and other SMEs to ensure solutions integrate effectively across the wider technology landscape
- Engage with clients and technical stakeholders to understand requirements, explain technical decisions and provide recommendations
- Troubleshoot complex data, performance and integration issues across development and production environments
- Define and promote data engineering standards, reusable patterns and best practices
- Mentor and support other engineers, encouraging knowledge sharing and continuous improvement
What We’re Looking For
- Significant hands‑on experience as a Data Engineer, ideally within complex enterprise environments
- Strong experience designing and delivering data solutions on AWS
- Strong knowledge of AWS data services such as S3, Glue, Lambda, Athena, Redshift and EMR, with experience selecting the right services for different requirements
- Strong Python and SQL skills
- Experience designing and building scalable ETL/ELT pipelines and data processing workflows
- Good understanding of data modelling, data lakes, data warehouses and modern data platform architectures
- Experience with infrastructure-as-code, ideally Terraform
- Experience with CI/CD and automated testing for data engineering workloads
- Good understanding of data security, governance, access control and data quality
- Experience making technical design decisions and providing engineering leadership within multidisciplinary teams
- Strong troubleshooting and problem‑solving skills
- Confidence working directly with clients and communicating technical concepts, decisions and recommendations
- Experience supporting and mentoring other engineers
- Current SC clearance is highly desirable given the nature and timescales of client engagements. Candidates must be eligible to obtain and maintain SC clearance.
- AWS certification at Associate or Professional level
- Experience with streaming and event‑driven data technologies
- Experience with technologies such as Spark, Kafka or Databricks
- Experience delivering data platforms within public sector, defence or other regulated environments
- Experience working within secure environments and understanding associated security and assurance requirements
- Exposure to machine learning or AI workloads and the data platforms that support them