NextGen Healthcare
Sr. Data Engineer
Remote Data Engineering role with clear candidate location fit.
PostedJul 2, 2026
Eligible countries1 accepted country
Seniority signalSenior
Work settingRemote
Accepted candidate locations
India
Role overview
Sr. Data Engineer
Requirements and responsibilities
Readable role content extracted into sections for faster review.
Data Engineering & Pipeline Development:
- Design, implement, and optimize ETL/ELT pipelines to support data ingestion and transformation from diverse healthcare data sources.
- Develop and maintain scalable data pipelines for real-time and batch processing to meet meet traditional BI applications and AI/ML needs.
- Work with structured, semi-structured, and unstructured data to create usable datasets for AI model training and deployment.
Database Management:
- Manage and optimize a variety of databases, including Postges, NoSQL, graph databases, and cloud-based databases like Snowflake and Redshift.
- Ensure efficient storage, retrieval, and integration of data across different systems.
AI Integration:
- Collaborate with data scientists and AI engineers to create datasets for a variety of use cases.
- Implement data annotation, curation, and augmentation techniques to enhance data readiness for AI/ML applications.
Healthcare Data Expertise:
- Apply knowledge of healthcare data standards such as HL7 and FHIR, ensuring adherence to HIPAA compliance and other regulatory requirements.
- Address challenges related to unstructured data extraction and large-scale data ingestion in EMR/EHR systems.
Collaboration & Innovation:
- Work closely with cross-functional teams, including healthcare specialists, business analysts and data architects to understand and address data needs.
- Ensure data quality, integrity, and security, especially when dealing with sensitive healthcare data.
Continuous Improvement:
- Stay updated with emerging technologies and frameworks in data engineering, AI, and healthcare.
- Contribute to the continuous improvement of processes and tools within the data engineering team.
Education Required:
- Bachelor’s degree (or higher) in Computer Science, Data Science, Artificial Intelligence, or a related field.
- Or, any combination of education and experience which would provide the required qualifications for the position.
Experience Required:
- 10+ years of proven experience in designing and building enterprise-grade ETL/ELT pipelines following modern architectural paradigms such as Data Lake, Lakehouse, and data mesh for high-volume analytics..
- Experience working with cloud platforms like AWS, Azure, or Google Cloud.
- Hands-on experience implementing star schema data models and orchestrating data pipelines to support scalable AI/ML model training and deployment.
- Hands on experience with ETL/ELT development using tools such as dbt, Fivetran, Spark, Snowpark including orchestration via Airflow or similar.
- Experience handling diverse data types and ensuring scalability in a complex environment.
Knowledge, Skills & Abilities:
- Knowledge of: Familiarity with big data frameworks such as Apache Spark, Kafka, and Hadoop. Understanding of data processing for voice, image, and text-based AI solutions. Familiarity with healthcare data standards and interoperability protocols. Knowledge of EMR/EHR systems and healthcare data management challenges along with healthcare data standards and coding systems (FHIR, HL7, ICD-10, CPT, etc.).
- Skill in: Strong programming skills in Python, and/or Scala, Java, and SQL. Excellent problem-solving and debugging skills. Strong communication.
- Ability to: Collaboration abilities to work with diverse stakeholders.
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