AWS Data Engineer

AWS Data Engineer

design, development, and maintenance

data lakes

data warehouses

analytics platforms

AWS data services

ETL development

data modeling

Key Responsibilities

• Design, develop, and maintain data pipelines and ETL workflows on AWS.
• Assist in building and managing data lakes and data warehouses for analytical and operational workloads.
• Support data ingestion, transformation, and integration from multiple sources.
• Collaborate with data architects and analysts to ensure data models align with business requirements.
• Implement data validation, monitoring, and logging mechanisms to ensure pipeline reliability.
• Work with cloud and DevOps teams to automate deployments using CI/CD frameworks.
• Ensure data security, governance, and compliance within AWS cloud environments.
  

Qualifications & Skills

• AWS Data Services: S3, Glue, Lake Formation, Redshift, Athena, Lambda
• ETL Development: AWS Glue (PySpark), SQL, or Python-based frameworks
• Data Modeling: Dimensional modeling, star/snowflake schema design
• Analytics & Query Tools: Redshift Spectrum, Athena, QuickSight (optional)
• Data Integration: API, CSV, Parquet, and streaming data ingestion
• Version Control & CI/CD: GitHub, CodeBuild, CodePipeline.
• Foundational understanding of IAM, KMS, and AWS security best practices
• Data Governance and Data Quality experience is must.
  

Preferred Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field
• 3–4 years of experience in data engineering or cloud data platform development
• Hands-on experience with AWS data and analytics services
• Solid understanding of ETL workflows, data pipelines, and data modeling principles
• Strong problem-solving, communication, and teamwork skills. Exposure to Life Sciences, Healthcare, or Pharmaceutical data environments
• Familiarity with GxP and HIPAA compliance for cloud data platforms
• AWS Certified Data Analytics – Specialty or AWS Certified Developer – Associate