Data Engineer, Analytics

Role Overview

The Data Engineer, Analytics will design and build scalable ETL/ELT pipelines, data models, and infrastructure to power analytics across a complex healthcare TPA platform. The role will work end-to-end, from ingestion through transformation, stakeholder collaboration, and automated reporting.

What You Will Do

Design and build scalable ETL/ELT pipelines, build data models and data marts, ensure data quality and integrity, optimize warehouse infrastructure, support data integration projects, write production SQL and Python, build reporting automation, conduct ad hoc analysis, and manage project workflows.

Why It Might Be a Fit

The ideal candidate will have 3+ years of experience in data engineering or analytics engineering, ideally within a TPA, healthcare, insurance, or claims processing environment, and experience working with large healthcare claims datasets.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field — or equivalent experience
• 3+ years of experience in data engineering or analytics engineering
• Experience working with large healthcare claims datasets
• Awareness of healthcare regulations including HIPAA, ACA, and CMS rules
• Strong SQL proficiency and experience in Python, Scala, or Java
• Hands-on experience with modern data warehouse platforms: Snowflake, Redshift, BigQuery, or Synapse
• Experience with cloud platforms and cloud-native data tools: AWS Glue, Azure Data Factory, Databricks, or equivalent
• Experience with data modeling concepts including star and snowflake schemas and dimensional modeling
• Experience with BI and dashboard/visualization tools
• Familiarity with Smartsheet, Microsoft Office Suite, and Atlassian toolsets for project and documentation management