Capstone Integrated Solutions is hiring an experienced AWS Data Engineer with deep expertise in building and optimizing data lakes, ETL pipelines, and scalable data solutions. You will design modern data architectures that enable analytics, machine learning, and business intelligence across the company.
What You'll Do
- Design, develop, and maintain ETL workflows and pipelines using AWS Glue, Python, and Spark.
- Build and optimize data lakes on AWS leveraging S3, Lake Formation, and Glue Data Catalog.
- Implement best practices for data partitioning, schema evolution, and performance tuning in distributed environments.
- Collaborate with data scientists, analysts, and business stakeholders to deliver reliable, high-quality datasets.
- Develop and maintain metadata, data lineage, and governance standards within AWS data ecosystems.
- Monitor, troubleshoot, and optimize ETL processes for scalability, reliability, and cost-effectiveness.
- Integrate structured and unstructured data from multiple sources into centralized storage solutions.
- Ensure compliance with data security, privacy, and regulatory requirements.
- Contribute to the architecture and roadmap for enterprise data platforms and analytics solutions.
What We're Looking For
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or equivalent experience.
- 5+ years of experience in data engineering with a strong focus on AWS.
- Hands-on expertise with AWS Glue (ETL, Data Catalog, Job orchestration).
- Strong experience with Amazon S3, Lake Formation, Athena, Redshift, and IAM.
- Proficiency in Python, PySpark, or Scala for ETL development.
- Solid understanding of data warehousing, data lake architectures, and distributed computing.
Technical Stack
- AWS Services: AWS Glue, Amazon S3, AWS Lake Formation, AWS Athena, AWS Redshift, AWS IAM
- Languages & Frameworks: Python, Spark, PySpark, Scala
