Mid-Level Data Engineer – Healthcare Domain

CareEco; Hyderabad; On-site; INR 800,000 - 1,200,000; Full time

Job summary

CareEco is seeking a motivated Mid-Level Data Engineer in Hyderabad, India, to design and optimize data pipelines in the healthcare domain. The ideal candidate has 2–3 years of experience with Databricks, SQL, and healthcare data standards like HL7.

Key responsibilities include maintaining scalable ETL/ELT pipelines and ensuring data quality. A Bachelor's degree in a relevant field is required, along with strong communication skills and familiarity with modern data architectures.

Qualifications

• 2–3 years of experience in a data engineering role, preferably in healthcare.
• Hands-on experience with Databricks, Apache Spark (PySpark), and SQL.
• Ability to work with structured and semi-structured data.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Databricks.
• Collaborate with data scientists and product managers.
• Implement data quality checks to ensure high data integrity.

Skills

Databricks

SQL

Apache Spark (PySpark)

Data quality checks

Healthcare data standards

Education

Bachelor’s degree in Business Administration, Healthcare Informatics, Information Systems, or a related field

Tools

Delta Lake

Git

Airflow

Azure Data Factory

dbt

Job description

About The Role

We are seeking a motivated and detail-oriented Mid-Level Data Engineer with 2–3 years of experience in designing, developing, and optimizing data pipelines within the healthcare domain. The ideal candidate will have hands‑on experience with Databricks, strong SQL skills, and a solid understanding of healthcare data standards (e.g., HL7, EDI X12 – 837/835, HCC, CPT/ICD codes).

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, PySpark, and Delta Lake for large-scale healthcare datasets.
• Collaborate with data scientists, analysts, and product managers to understand data requirements and deliver clean, reliable data.
• Ingest, process, and transform healthcare-related data such as claims (837/835), EHR/EMR, provider/member, and clinical datasets.
• Implement data quality checks, validations, and transformations to ensure high data integrity and compliance with healthcare regulations.
• Optimize data pipeline performance, reliability, and cost in cloud environments (preferably Azure or AWS).
• Maintain documentation of data sources, data models, and transformations.
• Support analytics and reporting teams with curated datasets and data marts.
• Adhere to HIPAA and organizational standards for handling PHI and sensitive data.
• Assist in troubleshooting data issues and root cause analysis across systems.

Required Qualifications

• 2–3 years of experience in a data engineering role, preferably in the healthcare or healthtech sector.
• Hands‑on experience with Databricks, Apache Spark (PySpark), and SQL.
• Familiarity with Delta Lake, data lakes, and modern data architectures.
• Solid understanding of healthcare data standards: EDI 837/835, CPT, ICD‑10, DRG, or HCC.
• Experience with version control (e.g., Git), CI/CD workflows, and task orchestration tools (e.g., Airflow, Azure Data Factory, dbt).
• Ability to work with both structured and semi‑structured data (JSON, Parquet, Avro, etc.).
• Strong communication skills and ability to collaborate in cross‑functional teams.

Education

• Bachelor’s degree in Business Administration, Healthcare Informatics, Information Systems, or a related field.