Data Engineer transforming data for analysis in an insurance company. Responsible for building data infrastructures and optimizing data delivery.
About the role
- Senior Data Engineer leading integration of Snowflake with Salesforce Health Cloud for healthcare analytics. Building robust data pipelines and ensuring seamless ETL processes.
Responsibilities
- Architect and implement ETL/ELT pipelines to ingest and transform data from Snowflake to SFDC Health Cloud.
- Design and maintain data models that support payer and provider analytics, including Portico, Excelys, and Amisys structures.
- Leverage DBT for transformation workflows and documentation of data lineage.
- Design and implement Snowflake clusters using Terraform.
- Use Pandas and Python for data wrangling, preprocessing, and validation.
- Collaborate with cross-functional teams to align integration efforts with business goals, including real-time sync and batch processing.
- Ensure data quality, governance, and compliance with healthcare regulations.
- Monitor pipeline performance and troubleshoot issues across environments.
- Contribute to platform scalability and observability using tools like MuleSoft, Informatica, and Salesforce APIs.
Requirements
- 5+ years of experience in data engineering, preferably in healthcare or CRM integrations.
- Hands-on experience with Snowflake, DBT, and Pandas.
- Strong SQL and Python skills.
- Experience with Salesforce Health Cloud data structures and APIs.
- Familiarity with the Health Care Industry, HIPAA and PII data management.
- Familiarity with integration platforms such as MuleSoft, Informatica, or custom Snowflake connectors.
- Experience with Master Data Management solutions and Data Management concepts. Entity resolution, splits, merges, data lineage.
- Understanding of healthcare data domains including eligibility, claims, care plans, and provider networks.
- Excellent problem-solving and communication skills.
- Deep SQL, stored procedure and materialized view experience.
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