Senior Data Engineer - INDIA

• Design, develop, and maintain scalable data pipelines using Python, PySpark, and other modern programming languages to support both batch and streaming workloads
• Build and optimize data processing frameworks on cloud platforms such as Databricks or Snowflake, ensuring performance, reliability, and cost efficiency
• Design and implement robust data models, including transactional (OLTP) and dimensional (OLAP) schemas, to support analytics, reporting, and application integration
• Develop high quality SQL code including complex queries, stored procedures, and views, with a focus on performance tuning and efficient data access patterns
• Create and manage workflow orchestration using Apache Airflow or similar tools, ensuring reliable scheduling, dependency management, and monitoring
• Implement and enforce data governance and metadata standards through tools such as Microsoft Purview, including data lineage, classification, cataloging, and security policies
• Build automated data quality and validation frameworks to ensure accuracy, completeness, and reliability of production datasets
• Collaborate with cross functional teams including data architects, analysts, scientists, and business stakeholders to understand requirements and deliver scalable, well designed data solutions
• Lead technical design sessions and code reviews, promoting engineering best practices, reusability, and maintainability
• Support cloud infrastructure and DevOps practices, including CI/CD pipelines, version control, testing automation, and environment management
• Monitor and troubleshoot production data pipelines, proactively addressing issues, performance bottlenecks, and system failures
• Contribute to the evolution of the enterprise data platform, recommending tools, frameworks, and architectures to improve scalability and efficiency

Work From Home, Data Management, Python Programming/Scripting Language, Programming Languages, Scalable System Development, Data Processing, Cloud Computing, OLAP (OnLine Analytical Processing), Transaction Processing/Management, Data Modeling, * 5+ years of experience in data engineering, software engineering, or similar disciplines

• Hands-on experience with Databricks or Snowflake
• Experience with orchestration tools such as Apache Airflow
• Experience working with cloud ecosystems (Azure preferred; AWS/GCP acceptable)
• Advanced SQL skills and experience with OLTP and OLAP data modeling
• Solid understanding of modern data warehousing, data lake, and ELT/ETL design patterns
• Familiarity with data governance tools, especially Microsoft Purview
• Solid programming expertise in Python, PySpark, or similar languages, * Healthcare industry experience, including claims, clinical, FHIR, HL7, or provider data
• Experience with containerization (Docker, Kubernetes) for data workloads
• Experience supporting machine learning workflows or analytical data science pipelines
• Knowledge of distributed computing concepts and performance tuning