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[Remote] Data Engineer – Healthcare Analytics Platform

Remote · USA Full-time New today

Note: The job is a remote job and is open to candidates in USA. Guidehouse is a consulting firm that specializes in data engineering and analytics solutions for various sectors, including healthcare. They are seeking a Data Engineer to support the design and development of an enterprise Contract Performance Analytics platform, focusing on data architecture, pipeline development, and integration of healthcare data.

Responsibilities

  • Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and load healthcare data from diverse structured and unstructured sources
  • Develop pipelines to process data from CMS and payer files (CCLF, paid claims, PUG) as well as Epic (Caboodle, Clarity) data models and extracts
  • Build and optimize data models to support analytics, reporting, and operational use cases, including BI and downstream analytics consumption
  • Transform raw data into standardized, analytics-ready canonical data models and curated data marts
  • Build lakehouse/medallion architecture, data ingestion patterns, and orchestration frameworks
  • Implement and maintain CI/CD pipelines for data engineering workflows, including pipelines and scheduled jobs, using version control and automation tools
  • Collaborate with database administrators, analysts, and application teams to integrate data sources, design schemas, and support downstream data consumers
  • Ensure data quality, integrity, and accuracy through validation, monitoring, logging, and alerting
  • Support data migration, integration, and modernization initiatives, including legacy system upgrades, optimization of large-scale ETL pipelines, query performance, and cloud adoption efforts
  • Troubleshoot and resolve issues in development and production environments to maintain stable and reliable data pipelines
  • Document data flows, pipelines, test cases, and technical solutions to support knowledge sharing and compliance requirements
  • Stay current with emerging tools, technologies, and best practices in data engineering and cloud platforms

Skills

  • US Citizenship or a Green Card is required
  • Bachelor's degree in Computer Science, Data Analytics, Software Engineering, Information Systems, or related fields
  • A minimum of FIVE (5) years of experience in data engineering, ETL/ELT development, or data platform engineering in a healthcare setting
  • Experience working with healthcare data, including claims, clinical, payer, or population health datasets
  • Experience working with healthcare data interoperability standards (e.g., FHIR, HL7)
  • Proficiency in Python and SQL for data engineering and transformation workloads
  • Hands-on experience designing and building ETL/ELT pipelines and data ingestion frameworks
  • Experience working with modern cloud data platforms or ETL/ELT tools (e.g., Databricks, Azure Data Factory, AWS Glue)
  • Experience working with lakehouse or medallion-style architectures for analytics platforms
  • Strong knowledge of relational database design, data warehouses, and/or data lakes (e.g., star/snowflake schemas)
  • Experience working with relational and/or distributed data systems, including data modeling
  • Experience working in a cloud environment (AWS or Azure) supporting data solutions
  • Experience with CI/CD practices and version control tools (e.g., Git)
  • Experience using monitoring and logging tools to support data pipeline reliability
  • Experience working with PHI and healthcare data privacy/security requirements
  • Ability to work effectively in an Agile development environment
  • Strong analytical and troubleshooting skills, and the ability to communicate technical concepts clearly to clients, engineers, and business stakeholders
  • Ability to work independently in a fast-paced, client-facing environment
  • Previous experience working with Epic and/or Athena in a healthcare setting for data engineering
  • Previous experience with Exasol or similar analytics platform
  • AWS, Azure, Databricks, Snowflake or other data engineering–related certifications
  • Experience with data visualization or analytics tools (e.g., Tableau, Power BI)
  • Exposure to microservices-based architectures or AI/ML-enabled data pipelines
  • Prior consulting experience

Benefits

  • Medical, Rx, Dental & Vision Insurance
  • Personal and Family Sick Time & Company Paid Holidays
  • Position may be eligible for a discretionary variable incentive bonus
  • Parental Leave and Adoption Assistance
  • 401(k) Retirement Plan
  • Basic Life & Supplemental Life
  • Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
  • Short-Term & Long-Term Disability
  • Student Loan PayDown
  • Tuition Reimbursement, Personal Development & Learning Opportunities
  • Skills Development & Certifications
  • Employee Referral Program
  • Corporate Sponsored Events & Community Outreach
  • Emergency Back-Up Childcare Program
  • Mobility Stipend

Company Overview

  • Guidehouse offers consulting services for public and commercial markets with expertise in management, technology, and risk consulting. It was founded in 2018, and is headquartered in Washington, District of Columbia, USA, with a workforce of 10001+ employees. Its website is https://guidehouse.com.
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