Neoware Technology Solutions - AWS Data Engineer - Python/SQL/ETL

Job Title :

Experience Level :

Location :

About the Role :

• Design, develop, and optimize scalable data pipelines (ETL/ELT) to ingest, transform, and load diverse healthcare data from various sources into our data warehouse/lake.
• Build and maintain robust data models (e.g., star schema, snowflake schema) to support analytics, reporting, and machine learning initiatives.
• Write highly optimized SQL queries and Python scripts for data manipulation, cleansing, validation, and transformation.
• Ensure data quality, integrity, and reliability across all data pipelines.
• Collaborate with data scientists, ML engineers, and business stakeholders to understand data requirements and translate them into efficient data solutions.
• Implement and manage data governance policies, security measures, and access controls for sensitive healthcare data (e.g., HIPAA compliance).
• Monitor data pipeline performance, troubleshoot issues, and implement solutions for continuous improvement.
• Automate data workflows using orchestration tools and integrate with CI/CD pipelines.
• Contribute to the selection, evaluation, and implementation of new data technologies and tools.
• Document data pipelines, data models, and data flow processes thoroughly.
  

Required Technical Skills

• Programming Language : Strong proficiency in Python for data processing and automation.
• Databases : Expert-level SQL skills for complex querying, data manipulation, and optimization. Experience with relational and NoSQL databases.
• Data Pipelines : Proven experience designing and implementing ETL/ELT processes.
• Cloud Platforms : Extensive hands-on experience with data services on AWS o (e.g., AWS S3, Redshift, Glue, EMR, Athena)
• Containerization : Familiarity with Docker for deploying data-related applications.
• Version Control : Proficient with Git and GitHub.
• Testing : Experience with Python unittest framework and Pytest for data pipeline testing.
• CI/CD : Understanding of CI/CD concepts and experience integrating data pipeline deployments with AWS CodePipeline or alternatives.
• Data Modeling : Strong knowledge of data warehousing concepts and data modeling techniques.