Senior AWS Data Engineer

• Design, build and maintain scalable data platforms and data pipelines within AWS
• Develop ETL/ELT processes for ingesting, transforming and processing data from multiple sources
• Implement data solutions using AWS S3, Glue, Lambda, Athena, Redshift, EMR and related technologies
• Design data models and storage approaches for analytical and operational requirements
• Develop solutions using Python, SQL and modern data engineering frameworks
• Apply infrastructure-as-code and automation to deploy and manage data platforms
• Build data quality, validation, monitoring and observability into engineering solutions
• Address security, governance and data protection requirements throughout solution design and delivery
• Collaborate with architects, cloud engineers, security specialists, SMEs and client teams
• Engage 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 engineers and encourage knowledge sharing and continuous improvement
• Contribute to technical decisions and provide technical ownership and engineering leadership

Requirements

• 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 including S3, Glue, Lambda, Athena, Redshift and EMR
• Strong Python and SQL skills
• Experience designing and building scalable ETL/ELT pipelines and data processing workflows
• 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
• 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
• Candidates must be eligible to obtain and maintain SC clearance
• AWS certification at Associate or Professional level is desirable
• Experience with streaming and event-driven data technologies is desirable
• Experience with Spark, Kafka or Databricks is desirable
• Experience in public sector, defence or other regulated environments is desirable
• Experience working within secure environments and understanding security and assurance requirements is desirable
• Exposure to machine learning or AI workloads and supporting data platforms is desirable

Core Competencies

Demonstrates expertise in designing and implementing scalable data platforms and ETL/ELT processes using AWS technologies, Python, and SQL. Strong focus on data security, governance, and quality, along with the ability to mentor engineers and lead technical decisions.

Highest-signal resume keywords

• AWS Data Services
• Python Programming
• SQL Proficiency
• ETL/ELT Pipeline Development
• Infrastructure-as-Code

Hard Skills

• Data Engineering
• Data Modelling
• Data Warehousing
• Data Lakes
• CI/CD
• Automated Testing
• Data Quality
• Troubleshooting
• Problem-Solving
• Technical Design Decisions

Soft Skills

• Client Engagement
• Communication
• Mentoring
• CollaborationLeadership

Certifications & Qualifications

• AWS Certification (Associate or Professional Level)
• SC Clearance Eligibility

Industry Keywords

• Public Sector
• Defence
• Regulated Environments
• Security Assurance
• Machine Learning
• AI Workloads

Tools & Technologies

• AWS S3
• AWS Glue
• AWS Lambda
• AWS Athena
• AWS Redshift
• AWS EMR
• Terraform
• Spark
• Kafka
• Databricks