AWS Data Engineer

We are seeking an experienced AWS Data Engineer to design, develop, and optimize cloud-based data solutions. The ideal candidate has strong hands-on experience with AWS data services, scalable ETL/ELT pipelines, and modern data architecture patterns. You will work collaboratively with analytics, engineering, and business teams to support data-driven decision-making.

• Design and develop scalable ETL/ELT pipelines using AWS services (Glue, Lambda, EMR, Step Functions, ECS/Fargate).
• Build and maintain data lakes and data warehouses using S3, Redshift, Athena, and Lake Formation .
• Optimize data workflows for performance, reliability, and cost efficiency.
• Implement data quality, validation, and monitoring frameworks.
• Collaborate with data scientists, BI engineers, and analysts to deliver accessible and reliable datasets.
• Automate pipeline deployment using CI/CD tools (CodePipeline, GitHub Actions, etc.).
• Ensure data governance, compliance, and security following AWS best practices (IAM, KMS, VPC).
• Troubleshoot and resolve issues across data pipelines and AWS environments.

• 3+ years of experience as a Data Engineer , preferably in AWS environments.
• Strong hands-on experience with AWS data services (Glue, S3, Athena, Lambda, Redshift, EMR).
• Proficiency in Python or PySpark for data processing.
• Expert-level SQL skills for data modeling and optimization.
• Experience with distributed data processing (Spark, EMR, Databricks is a plus).
• Knowledge of CI/CD, version control (Git), and DevOps automation.
• Familiarity with data lake/lakehouse architecture and best practices.

• AWS certifications (AWS Data Analytics Specialty, AWS Solutions Architect, etc.).
• Experience with streaming data technologies (Kinesis, Kafka).
• Exposure to ML/AI workflows or MLOps tools.
• Experience with Terraform or CloudFormation for infrastructure-as-code.
• Knowledge of BI tools such as QuickSight, Power BI, or Tableau.

• Competitive compensation and benefits.
• Opportunity to work with modern cloud and data engineering technologies.
• Learning, certification, and career development support.
• Collaborative, growth-focused working environment.