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.
Job title
Lead Data Engineer – Snowflake, DBT, Databricks, Pandas
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