Data Engineer III

Location: Remote – United States

Employment Type: Long-Term Contract / Potential Contract-to-Hire

Client: LaunchCode Client Partner – Enterprise Healthcare Organization

Position Overview

LaunchCode is seeking an experienced Data Engineer III for a client partner in the healthcare industry. This role will focus on building and managing enterprise Data Supply Chain pipelines that support operational, analytical, real-time data exchange, and AI-readiness initiatives.

The ideal candidate is a hands-on Data Engineer with strong experience designing ETL/data pipelines, integrating complex data sources, and working within modern cloud data environments including Databricks and Snowflake.

What You’ll Do

• Design, build, maintain, and optimize enterprise Data Supply Chain pipelines supporting operational and analytical needs.
• Manage both real-time data flows and high-volume/bulk data exchange.
• Develop data integration and transformation solutions using Databricks, Snowflake/Snowpipe, and modern ETL technologies.
• Apply strong historical ETL experience using tools such as Informatica or Talend.
• Transform and model structured and semi-structured data, including JSON, XML, flat files, FHIR, HL7, and relational database data.
• Build pipelines that move data into Databricks and relational structures within Snowflake.
• Support application-to-application and database-to-database integrations.
• Design and support APIs that enable enterprise data access and integration.
• Work with cloud and data technologies including AWS S3, MongoDB, GraphDB, Databricks, and Snowflake.
• Establish and follow standards for data modeling, data quality, security, metadata, completeness, and end-to-end integration.
• Support development of a Longitudinal Health Record, enabling enterprise access to healthcare data for operational, analytical, and AI use cases.
• Help ensure enterprise data is accessible, trustworthy, standardized, and prepared for future AI initiatives.
• Potentially support API accessibility and data services through MongoDB.

Technical Environment

Strong experience with several of the following is expected:

• Databricks
• Snowflake / Snowpipe
• ETL and enterprise data pipeline engineering
• Informatica and/or Talend
• SQL and relational data structures
• AWS S3
• MongoDB
• Graph databases / GraphDB
• JSON
• XML
• Flat-file processing
• API development and integration
• Application-to-database and database-to-database integration
• FHIR
• HL7 V3 / V4
• Data modeling
• Data quality and governance
• Metadata and security standards

Healthcare data experience, particularly working with FHIR, HL7, longitudinal healthcare records, or healthcare interoperability, is highly valuable.

AI / Modern Engineering Environment

The organization is also incorporating AI-assisted engineering capabilities. Exposure to or awareness of tools such as Devin, Windsurf, and AI capabilities within Databricks is beneficial.

This does not need to be an AI Engineer, but the ideal candidate should be comfortable working in an engineering organization increasingly using AI-assisted development tools.

What We’re Really Looking For

This position requires more than familiarity with a list of technologies.

Candidates should be able to clearly explain:

• A data pipeline they personally designed or built
• Where the data originated and where it ultimately landed
• How data was ingested, transformed, modeled, and validated
• Whether the pipeline handled batch, bulk, or real-time data
• The ETL tools and architecture they selected and why
• How they handled data quality and failures
• How APIs or databases were integrated
• Their specific hands-on responsibilities
• What went wrong and how they troubleshot it
• How they worked with Databricks, Snowflake, Informatica, Talend, or comparable technologies in a production environment

We are looking for someone who can walk through the engineering from source to destination, not simply identify the technologies on their résumé.