Job highlights

- Bachelors degree in Computer Science,Information Systems,Data Engineering,Engineering,Healthcare Informatics,or a related field is required
- Experience extracting,integrating,and migrating data from Teradata,SQL Server,file-based sources,GCP Datamarts,and other enterprise data sources into GCP-based data platforms
- . Must Have Skills
- . Education Experience

Job Summary Data Engineer to support the HIM Datamart used by Parallon HIM Operations. This critical role is responsible for creating, maintaining, monitoring, and supporting data pipelines that pull data from Teradata, multiple SQL Server environments, various GCP Datamarts, and other enterprise data sources into the HIM GCP Datamart.

The successful candidate will design and support ETL and ELT processes using Airflow, DAGs, Google Cloud Dataproc, Python, PowerShell, SSIS, SQL, and other data integration technologies. The ideal candidate must be comfortable supporting production data pipelines, troubleshooting complex data issues, improving data quality, and ensuring timely and accurate data availability for HIM operations.

This position is best suited for a data engineering professional who can balance development, production support, automation, data quality, cloud data engineering, documentation, and operational reliability in a critical healthcare operations environment.

Responsibilities

- Design, develop, maintain, and support ETL/ELT data pipelines for the HIM GCP Datamart. Extract, transform, and load data from Teradata, SQL Server, GCP Datamarts, and other enterprise data sources into HIM data platforms.
- Develop and support data workflows using Airflow, DAGs, Dataproc, Python, PowerShell, SSIS, SQL, and related data integration tools.
- Create, schedule, monitor, and troubleshoot Airflow DAGs for recurring data ingestion, transformation, validation, reconciliation, and delivery processes.
- Develop and optimize SQL queries, stored procedures, views, functions, and transformation logic across SQL Server, Teradata, PostgreSQL, BigQuery, and other relational platforms.




- Support on-premise to GCP data integration using Google Cloud Dataproc and related GCP services for large-scale data processing and transformation.
- Monitor data pipelines for failures, delays, performance issues, data quality problems, schema changes, and source system impacts.
- Troubleshoot production data issues, including missing data, late-arriving files, failed jobs, transformation errors, data mismatches, and performance bottlenecks.
- Perform root cause analysis and implement long-term fixes to improve pipeline reliability, reduce recurring failures, and improve operational stability.
- Implement data validation, reconciliation, and quality checks to ensure HIM data is complete, accurate, consistent, and timely.
- Collaborate with Parallon HIM Operations, source system owners, and technical teams to understand data needs, dependencies, refresh schedules, reporting impacts, and business priorities.
- Create and maintain data pipeline documentation, data flow diagrams, source-to-target mappings, job schedules, support procedures, and operational runbooks.
- Participate in release management, change control, defect resolution, enhancement delivery, incident response, and production support activities.
- Improve automation, monitoring, alerting, logging, and operational visibility across HIM data pipelines.
- Ensure data engineering solutions follow enterprise standards for security, privacy, compliance, data governance, change control, and production readiness.
- Identify opportunities to modernize legacy ETL processes and improve scalability, maintainability, reliability, and cost efficiency.

Education Experience

- Bachelor's degree in Computer Science, Information Systems, Data Engineering, Engineering, Healthcare Informatics, or a related field is required.




- Five or more years of experience in data engineering, ETL/ELT development, data warehousing, data integration, or supporting enterprise data platforms, data marts, data lakes, or operational data stores.
- Strong hands-on experience designing, developing, maintaining, and troubleshooting production data pipelines using SQL, Python, PowerShell, SSIS, Apache Airflow, DAGs, and other ETL/ELT technologies.
- Strong SQL experience across SQL Server, Teradata, PostgreSQL, BigQuery, or similar platforms, including complex queries, joins, aggregations, stored procedures, views, functions, performance tuning, and source-to-target validation.
- Experience extracting, integrating, and migrating data from Teradata, SQL Server, file-based sources, GCP Datamarts, and other enterprise data sources into GCP-based data platforms.
- Experience with Google Cloud Platform data services, including Dataproc, Cloud Composer, Cloud Storage, BigQuery, Cloud SQL, Cloud Logging, and Cloud Monitoring.
- Experience with batch processing, job scheduling, dependency management, error handling, logging, alerting, data validation, reconciliation, data quality checks, and production support for critical business operations.
- Experience with file-based integrations, including CSV, fixed-width files, Excel, JSON, XML, Parquet, Avro, and delimited files.
- Experience with CI/CD and source control practices using GitHub, Azure DevOps, Git, YAML pipelines, or similar tools.
- Solid analytical, troubleshooting, problem-solving, written communication, and verbal communication skills, with the ability to work independently and collaboratively with technical and business teams.

Must Have Skills

- Spark

- PySpark

- Hadoop
- Teradata SQL
- data ingestion frameworks

- CDC patterns
- SCD handling
- data modeling
- data pipeline observability

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior - Data Engineer (Hyderabad)
🏢 HCA Healthcare UK
📍 Hyderabad