Data Engineer

• Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
• Build and optimize data ingestion frameworks from multiple source systems, APIs, databases, and cloud platforms.
• Develop and maintain enterprise data models, data warehouses, and data lakes.
• Ensure high levels of data quality, integrity, security, and governance across data platforms.
• Collaborate with business analysts, architects, data scientists, and application teams to understand data requirements.
• Implement data transformation, validation, reconciliation, and monitoring processes.
• Optimize performance of large-scale data pipelines and database workloads.
• Support analytics, reporting, AI/ML, and advanced data science initiatives through reliable data delivery.
• Implement metadata management, lineage tracking, and data cataloging solutions.
• Troubleshoot production issues and perform root cause analysis for data-related incidents.
• Participate in code reviews, architecture discussions, and technical design sessions.
• Ensure adherence to healthcare regulatory and compliance requirements, including HIPAA and data privacy standards.
• Work with distributed teams across multiple locations and support enterprise-scale data initiatives.

• Strong expertise in cloud-based data engineering, ETL/ELT development, and big data technologies.
• Experience working in healthcare environments.
• Proficiency in AWS (Glue, EMR, Lambda, S3, Redshift, Athena) or Azure (ADF, Data Lake, Synapse, Databricks).
• Experience with databases such as SQL Server, Oracle, PostgreSQL, or Snowflake.
• Strong programming skills in Python, SQL, PySpark, and Shell Scripting.
• Knowledge of Big Data Technologies including Apache Spark and Hadoop Ecosystem.
• Experience with DevOps and CI/CD tools like Git and Jenkins/Azure DevOps.
• Familiarity with Agile/Scrum methodology.
• Knowledge of healthcare data standards such as HL7, FHIR, ICD, and CPT is preferred.
• Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Engineering, or related field., * Experience in Healthcare, Health Insurance, or Life Sciences domain.
• Exposure to AI/ML data pipelines and MLOps frameworks.
• Experience with Kafka.
• Experience with Snowflake, Databricks, or modern cloud-native data platforms.

Skills:

• Data Engineering.
• Data Pipeline Development.
• ETL/ELT Design.
• Data Warehousing.
• Dimensional & Relational Data Modeling.
• Data Lake Architecture.
• Data Quality.
• Data Governance.
• AWS.
• Azure.
• Python.
• SQL.
• PySpark.
• Apache Spark.
• CI/CD.

Qualification And Education:

• Strong analytical and problem-solving skills.
• Excellent communication and presentation skills.
• Ability to communicate effectively with stakeholders.
• Ability to work independently in fast-paced environments.
• Strong collaboration and mentoring capabilities.