EIM Data Engineer @ Virtusa

Job Description

• The Data Engineer designs and builds the automated ETL/ELT workflows that power Mercers consulting tools
• You will be responsible for ingesting fragmented data from insurance carriers, third-party administrators (TPAs), and client HRIS systems, transforming it into a structured format for actuarial modeling and compensation benchmarking

Key Responsibilities

• Pipeline Development: Build and maintain robust data pipelines using Python, SQL, and Spark to process large-scale healthcare claims and salary survey data
• Data Normalization: Develop logic to clean and standardize diverse data formatsLanguages: Expert-level SQL and Python (specifically for data manipulation via Pandas/PySpark)
• Big Data Tools: Hands-on experience with Databricks, Snowflake, or Hadoop ecosystems
• Orchestration: Experience with Airflow or Azure Data Factory for managing complex job dependencies
• Modeling: Understanding of Star/Snowflake schemas and Data Vault 20 for long-term analytical storage
• As a Data Engineer for Mercers Health Benefits (HB) and Compensation domain, you are the architect of the Data Highway
• Your mission is to build the pipelines that move millions of sensitive recordsfrom hospital claims to executive payrollinto a centralized, high-performance analytics environment
• Job Title: Data Engineer Health Total RewardsRole Objective by building automated masking and de-identification routines to ensure HIPAA and GDPR compliance for Protected Health Information (PHI)
• Cloud Infrastructure: Deploy and monitor data workloads on Azure (Data Factory/Databricks) or AWS (Glue/Redshift) to ensure high availability and scalability
• Technical Stack RequirementsLanguages: Expert-level SQL and Python (specifically for data manipulation via Pandas/PySpark)
• Big Data Tools: Hands-on experience with Databricks, Snowflake, or Hadoop ecosystems
• Orchestration: Experience with Airflow or Azure Data Factory for managing complex job dependencies
• Modeling: Understanding of Star/Snowflake schemas and Data Vault 20 for long-term analytical storage

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Keyskills:   data engineer snowflake python hris data pipelines airflow databricks elt data engineering sql pandas redshift spark hadoop big data aws etl azure