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AWS Engineer

24 hours ago

Mississauga, Ontario, Canada Cognizant Technology Solutions Full time
AWS Data Engineer
Job Summary

The AWS Data Engineer is responsible for designing, building, and optimizing scalable data pipelines and cloud-native data solutions on Amazon Web Services (AWS). This role requires strong expertise in AWS data services, ETL/ELT development, SQL, Python, and data modeling. You will collaborate with cross-functional teams to deliver high-quality, reliable, and secure data solutions that support analytics, reporting, and data-driven decision-making.

Key Responsibilities
Data Engineering & Pipeline Development
  • Design, develop, and maintain scalable ETL/ELT pipelines using AWS services such as Glue, Lambda, EMR, Step Functions, and Data Pipeline.
  • Build and optimize data ingestion frameworks for structured and unstructured data.
  • Implement data transformation logic using Python, PySpark, and SQL.
  • Develop and maintain conceptual, logical, and physical data models to support analytics and reporting.
Cloud Architecture & AWS Services
  • Work with AWS services including S3, Redshift, Glue Catalog, Athena, DynamoDB, Kinesis, and IAM.
  • Optimize data storage, retrieval, and compute performance across AWS environments.
  • Implement best practices for scalability, cost optimization, security, and reliability.
Data Mapping & Governance
  • Perform Source-to-Target data mapping to ensure accurate data lineage, traceability, and alignment with business requirements.
  • Execute data validation, profiling, and quality checks to ensure accuracy and completeness.
  • Support data governance initiatives through metadata management, standards enforcement, and documentation.
Collaboration & Stakeholder Engagement
  • Collaborate with data analysts, data scientists, architects, and business stakeholders to understand data needs.
  • Translate business requirements into technical specifications and scalable data solutions.
  • Prepare clear documentation and presentations to communicate technical concepts and project status.
Continuous Improvement & Innovation
  • Identify opportunities to automate data engineering workflows and improve operational efficiency.
  • Stay current with AWS innovations, big data technologies, and industry best practices.
  • Contribute to architectural discussions and long-term data platform strategy.
Required Qualifications
  • Strong experience with AWS data services such as Glue, Redshift, S3, Lambda, EMR, Athena, and Kinesis.
  • Proficiency in Python, SQL, and PySpark.
  • Hands-on experience with ETL/ELT development and orchestration.
  • Strong understanding of data warehousing concepts and dimensional data modeling.
  • Experience with CI/CD pipelines and version control tools such as Git, CodePipeline, and CodeBuild.
  • Knowledge of data governance, metadata management, and Source-to-Target mapping.
  • Experience working in Agile/Scrum environments.
Preferred Qualifications
  • Experience with infrastructure-as-code tools such as Terraform or CloudFormation.
  • Exposure to streaming technologies including Kafka or Amazon Kinesis.
  • Knowledge of containerization technologies such as Docker, ECS, or EKS.
  • Experience with BI and visualization tools such as Power BI or Amazon QuickSight.
Certifications (Recommended)
  • AWS Certified Data Engineer – Associate
  • AWS Certified Solutions Architect – Associate
  • AWS Certified Developer – Associate