Data Engineer 2

5 days ago

Hyderabad, Telangana, India Modernizing Medicine, Inc. Full time ₹ 15,00,000 - ₹ 25,00,000 per year

We are looking for a Data Engineer 2 to support our growing AI initiatives in the Revenue Cycle Management (RCM) and KLARA domain. The ideal candidate will have strong experience in building scalable data pipelines, handling complex data transformations, and ensuring data readiness for machine learning and analytics models. You will work closely with data scientists and analysts to deliver high-quality, production-ready datasets and pipelines.

Key Responsibilities:

  • Design, develop, and maintain scalable ETL/ELT pipelines to support AI/ML workflows in the RCM space.

  • Work with structured and semi-structured data from diverse healthcare and financial systems.

  • Build and optimize data ingestion and transformation logic using PySpark, Python, and SQL.

  • Implement and manage DataOps pipelines, including data quality checks, logging, monitoring, and automated testing.

  • Schedule and orchestrate pipelines using tools like Airflow, Databricks Workflows, or Azure Data Factory.

  • Optimize SQL queries and Spark jobs to ensure performance and cost-efficiency.

  • Collaborate with data scientists to ensure timely delivery of clean, well-structured data for model development and deployment.

  • Ensure adherence to data governance, security, and compliance policies in healthcare data environments.

Must-Have Skills:

  • Strong proficiency in Python and PySpark for data processing

  • Advanced SQL skills, including query optimization and complex joins

  • Hands-on experience with data pipeline tools (e.g., Airflow, Databricks, ADF, Glue)

  • Experience building data pipelines for AI/ML use cases

  • Good understanding of data modeling, data validation, and error handling

  • Familiarity with healthcare or RCM data structures (claims, encounters, EDI 837, etc.) is a plus

Nice-to-Have Skills:

  • Knowledge of cloud data platforms (e.g., AWS Redshift, Azure Synapse, Snowflake)

  • Experience with CI/CD for data pipelines

  • Exposure to data versioning tools (e.g., DVC) or data cataloging systems

  • Familiarity with ML lifecycle and MLOps requirements

Educational Qualifications:

  • Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field

  • Certifications in cloud platforms (AWS, Azure) or data engineering tools are a plus

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