Job Summary:

The Data ETL / Data Engineer will design, develop, test, and maintain scalable data integration and ETL solutions, with a strong focus on SQL, Python, PySpark, data warehousing, and large-scale data processing. The role will work with modern cloud-based data platforms including Databricks, Snowflake, and PostgreSQL, while applying performance optimization, version control, CI/CD practices, and AI-powered development tools to deliver efficient and reliable data solutions in an onsite environment.

Key Responsibilities:

• Design, develop, test, and maintain ETL and data pipeline solutions.
• Build scalable data processing workflows using Python and PySpark.
• Develop and optimize

SQL/PLSQL

scripts for data extraction, transformation, and loading.

• Design and maintain data warehouse architectures and data models.
• Perform query performance tuning and optimization for large datasets.
• Develop and support data solutions across Databricks, Snowflake, and PostgreSQL environments.
• Manage source code repositories using Bitbucket/Git and follow CI/CD best practices.
• Leverage AI-powered development tools such as GitHub Copilot and Windsurf to improve productivity and code quality.
• Collaborate with business stakeholders, data analysts, and cross-functional teams to deliver data solutions.
• Create technical documentation and support production deployments.
• Develop shell scripts to support data engineering and operational activities as needed.
• Contribute to AI Agent development and AI-driven data solutions as required.

Required Qualifications:

• 5+ years of experience in data ETL and/or data engineering.
• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.
• Strong experience with ETL development, data integration, and data engineering.
• Hands-on experience with SQL/T-SQL, PL/SQL, Python, and PySpark.
• Strong experience with database development, data warehousing concepts, and development.
• Experience with query performance tuning and optimization.
• Knowledge of cloud-based data platforms and modern data engineering practices.
• Experience with Bitbucket/Git and modern version control practices.
• Experience leveraging AI development tools such as GitHub Copilot or Windsurf.
• Strong analytical, troubleshooting, and problem-solving skills.

Preferred Qualifications:

• Experience with Databricks and Snowflake.
• Experience with PostgreSQL, including AWS RDS PostgreSQL.
• Knowledge of AWS cloud services.
• Experience with shell scripting.
• Exposure to AI Agent development and Generative AI technologies.
• Experience working in Agile development environments.

Notes:

Mandatory Areas Must Have Skills Primary Skills

SQL & PL/SQL

Development Python Programming PySpark ETL Development and Data Integration Data Warehousing Concepts and Development Query Performance Tuning and Optimization Bitbucket/Git Version Control Experience leveraging AI tools such as

GitHub Copilot and Windsurf Secondary Skills:

Databricks Snowflake PostgreSQL (AWS RDS PostgreSQL) Developing AI Agents and AI-driven solutions Shell Scripting Domain Experience (If any)

• Good to have healthcare experience Must have Certifications
• None Location
• Remote Onsite Requirement
• Remote Number of days onsite
• Remote