Data Integration Developer

enGen Global; Hyderabad, Chennai District; On-site; INR 1,000,000 - 2,000,000; Full time

Job summary

enGen Global in Hyderabad seeks a Data Integration Developer to design, build, and maintain ETL pipelines for extracting membership, clinical, and claims data into JSON. Strong PySpark and healthcare interoperability are required to ensure scalable, accurate data flows.

You will collaborate with data architects and analysts, implement data quality checks, optimize PySpark jobs, document mappings, and support testing and deployment across cloud environments.

Qualifications

• PySpark with large-scale data processing capabilities.
• Experience with US healthcare data (membership, clinical, claims).
• Experience with HL7 or healthcare data interchange formats.

Responsibilities

• Design, develop, and maintain data integration pipelines to extract membership, clinical, and claims data from diverse source systems.
• Develop and optimize PySpark scripts for efficient data processing and transformation of structured and non-structured data.
• Collaborate with data architects, business analysts, and developers to understand data requirements.
• Implement robust data quality checks and validation processes to ensure data integrity.
• Troubleshoot and resolve data integration issues, including data discrepancies and performance bottlenecks.
• Participate in design and implementation of new data models as needed.
• Develop and maintain documentation for data integration processes, mappings, and specifications.
• Collaborate with cross-functional teams to support testing, deployment, and maintenance of data integration solutions.

Skills

PySpark

US Healthcare domain

HL7

Education

Bachelor's degree in Computer Science / IT / Data Science or related field

Tools

Informatica

Gen AI

Job description

Department

DataWorks, CMS Interoperability Mandate

Job Summary

We are seeking a highly skilled and motivated Data Integration Developer to join our team.

The ideal candidate will be responsible for designing, developing, and implementing solutions that extract, transform, and load (ETL) membership, clinical, and claims data from various source systems into a JSON format. This role requires strong expertise in PySpark and healthcare domain experience to ensure data accuracy, interoperability, and efficient data flow.

Responsibilities

• Design, develop, and maintain data integration pipelines to extract membership, clinical, and claims data from diverse source systems.
• Develop and optimize PySpark scripts for efficient data processing, transformation, and manipulation of large datasets (structured and non-structured).
• Work closely with data architects, business analysts, and other developers to understand data requirements
• Implement robust data quality checks and validation processes to ensure the integrity and accuracy of data
• Troubleshoot and resolve data integration issues, including data discrepancies, performance bottlenecks, and system errors.
• Participate in the design and implementation of new data models as needed.
• Develop and maintain comprehensive documentation for data integration processes, mappings, and technical specifications.
• Collaborate with cross-functional teams to support testing, deployment, and ongoing maintenance of data integration solutions.

Mandatory/Must Have Skillset

• PySpark: Extensive experience with PySpark for large-scale data processing
• US Healthcare domain
• Any HL7 work experience

Good to have

• Informatica
• Gen AI

Education

Bachelors degree in computer science, Information Technology, Data Science, or a related field.

Experience

• 5-12 years of experience in data integration, ETL development, or software engineering, with a focus on US healthcare data.
• Proven experience working with healthcare data (membership, clinical, claims).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) is a plus.

Soft Skills

• Excellent analytical and problem-solving skills.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with technical and non-technical stakeholders.
• Ability to work independently and as part of a team in a fast-paced environment.
• Detail-oriented with a commitment to data quality and accuracy.