Usage of Conventional AI
Virtusa utilizes Artificial Intelligence (AI) technology for the purpose of conducting candidate pre-employment assessments. This AI may include both text-based and voice-based functionalities. The AI technology will have access to the data that you upload or provide during your interaction with the AI bot and will use such data solely for the purpose of performing assessment in accordance with Virtusa policies and practices. The AI is not used to substantially assist or replace discretionary employment decisions. Read our full employee privacy policy here.
Job description
The Data Engineer designs and builds the automated ETL/ELT workflows that power Mercer’s 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 formats
Languages: 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 2.0 for long-term analytical storage.As a Data Engineer for Mercer’s Health & Benefits (H&B) and Compensation domain, you are the architect of the Data Highway. Your mission is to build the pipelines that move millions of sensitive records—from hospital claims to executive payroll—into 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 2.0 for long-term analytical storage.
QualificationsExperience: 3–6 years in Data Engineering, ideally within Healthcare, Insurance, or FinTech.Domain Knowledge: Familiarity with ICD-10/CPT codes (medical) or global payroll structures.Education: Bachelor’s degree in Computer Science, Data Engineering, or a related quantitative field.
Key job details
About Virtusa
Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 30,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.
Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.
Virtusa is an Equal Opportunity Employer. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government-issued ID during each interview. All candidates must be authorized to work in the USA.
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