Data Engineer - Remote

Title :   Data Engineer

Location :: St. Louis Park, MN (Remote)

Duration : Contract

Visa – USC

Client Need : Recent Healthcare exp and profile must be 10+

• We are seeking a Senior Data Engineer to design, build, and maintain scalable data platforms and pipelines supporting healthcare analytics, operational reporting, and AI/ML initiatives. This role will work closely with data architects, software engineers, analysts, and business stakeholders to deliver reliable, high-quality data solutions across the organization.

Responsibilities

• Design, build, and maintain scalable batch and streaming data pipelines.
• Ingest, transform, and integrate data from a variety of healthcare and operational source systems.
• Develop and optimize ETL/ELT processes to support analytics, reporting, and downstream applications.
• Build automated testing, monitoring, and validation processes to ensure data quality and reliability.
• Partner with business, analytics, and engineering teams to understand requirements and deliver data solutions.
• Troubleshoot and resolve data quality, performance, and integration issues.
• Maintain documentation for data lineage, transformation logic, and architecture.
• Identify opportunities to improve scalability, performance, and operational efficiency of data platforms.

Required Qualifications:

• 5+ years of experience in Data Engineering or a related field.
• Strong SQL skills.
• Hands-on experience with modern cloud-based data warehouses such as Snowflake, Redshift, BigQuery, or similar.
• Experience building production-grade data pipelines using Python, Scala, or Java.
• Experience with modern orchestration tools such as Airflow, Dagster, Prefect, or similar.
• Strong understanding of data modeling, ETL/ELT processes, and data architecture principles.
• Experience working in cloud environments and supporting enterprise-scale data platforms.
• Strong problem-solving, communication, and collaboration skills.

Preferred Qualifications:

• Healthcare industry experience.
• Experience supporting analytics, reporting, AI/ML, or operational data initiatives.
• Experience with DBT and modern analytics engineering practices.
• Familiarity with FHIR, healthcare interoperability, claims, clinical, or quality-related datasets.
• Experience working in regulated healthcare environments.