Job Description:

Key Responsibilities

• Develop product features to ingest and augment data about insurance Claims, Providers, Billing, Legal, Medical Images, etc from multiple sources
• Build frameworks to handle data at high scale using technologies like Apache Spark and data cataloging tools like Apache Hive, AWS Glue on top of a multi-tiered data lake storage
• Use exploration and analytic tools like Apache Zeppelin, AWS Athena/Presto on top of Apache Hive to probe and validate data
• Build ETL pipelines using Apache Airflow and integrate with multiple components and data sources and sinks
• Be an ardent code contributor to multiple product domains spanning insurance Claims, Bills, Providers and Attorneys affiliated with the claim to augment the data and help with Feature Engineering work for the AI modules
• Design and architect new product features and be a strong proponent of using up-to-date tools and help the team adopt such tools

Qualifications & Experience

• Candidates with 5+ years’ experience in data engineering, who have either obtained a Graduate degree in the field of Computer Science or related field, or Bachelor's degree with 7+ years of relevant experience in the above fields.
• Experience with the following software/tools is highly desired :
  • Apache Spark, Kafka, Hive, etc
  • SQL and NoSQL databases like MySQL, Postgres, DynamoDB
  • Workflow management tools like Airflow
  • AWS cloud services: RDS, AWS Lambda, AWS Glue, AWS Athena, EMR
  • Familiarity with Spark programming paradigms (batch and stream-processing)
  • RESTful API services
• Strong programming skills in at least one of the following languages: Java, Scala, C++. Familiarity with a scripting language like Python as well as Unix/Linux shells
• Experience implementing software around data processing, metadata management, ETL pipeline tools like Airflow
• Experience working with cross-functional teams in a fast-paced environment
• Knowledge of healthcare data pertaining to insurance claims is helpful
• Ability to translate data needs into detailed functional and technical designs for development, testing and implementation
• Ability to identify and communicate risks and issues affecting business rules, functional requirements and specifications
• Ability to serve as a liaison between technical, quality assurance and non-technical stakeholders throughout the development and deployment process.