Data Engineer, Onboarding

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Data Engineer, Onboarding based in the United States.

The Data Engineer, Onboarding will play a key role in integrating healthcare data into modern cloud-based platforms that support revenue cycle management and compliance initiatives. This position focuses on building reliable data pipelines, transforming complex healthcare records, and ensuring accurate data migration for customer implementations. You will work with technologies such as Databricks, PySpark, Python, and Snowflake to automate workflows and improve onboarding efficiency. Collaborating with Implementation, Product, Support, and IT teams, you will help deliver seamless data integration experiences for healthcare organizations. The role combines hands-on engineering with healthcare domain expertise, data quality management, and continuous process improvement. This fully remote opportunity is ideal for a detail-oriented data professional who wants to apply modern data engineering techniques to meaningful challenges in healthcare technology.

Accountabilities:

• Develop, implement, and maintain ETL/ELT data pipelines using Databricks, PySpark, and Python, following a Bronze/Silver/Gold lakehouse architecture.
• Ingest, parse, transform, and validate healthcare data, including 837 healthcare claims, 835 remittance advice, and electronic medical record (EMR) data, ensuring accurate mapping to the target platform's data model.
• Support data conversion and migration initiatives, including transitioning information from legacy systems such as Microsoft SQL Server to modern cloud-based data platforms.
• Build reusable automation tools and data processing workflows using Python, PySpark, and SQL to reduce manual onboarding activities and improve operational efficiency.
• Implement automated data validation, quality controls, and reconciliation procedures to identify inconsistencies, maintain data integrity, and resolve discrepancies promptly.
• Monitor and maintain customer data feeds and file-processing workflows following implementation, troubleshooting failures and ensuring reliable ongoing operations.
• Collaborate with Implementation, Product, Support, and IT teams to gather technical requirements, define data mappings, resolve integration challenges, and coordinate customer onboarding activities.
• Investigate data ingestion and integration issues, perform root-cause analysis, and escalate complex technical problems to senior engineering team members when necessary.
• Track assigned onboarding tasks and project milestones using project management tools such as Monday.com, providing regular progress updates and helping ensure timely delivery.
• Document data pipelines, transformation logic, data flows, and operational procedures to facilitate knowledge transfer and effective handoffs to Support teams.
• Apply appropriate data security, privacy, and access controls while adhering to HIPAA requirements and other relevant healthcare regulations.
• Contribute to continuous improvement initiatives by identifying opportunities to optimize pipeline performance, strengthen data quality, and standardize onboarding processes.
• Perform additional engineering and data integration responsibilities as needed to support team objectives.

Requirements

• Education: Bachelor's degree in Computer Science, Data Science, Health Informatics, Information Systems, or a related field, or equivalent practical experience.
• Professional experience: At least three years of experience in data engineering, ETL/ELT development, and data warehousing.
• Programming expertise: A minimum of two years of hands-on experience with Python and SQL, including data transformation, automation, and troubleshooting.
• Databricks and PySpark: At least one year of practical experience using Databricks and PySpark to develop, maintain, and optimize data pipelines.
• Data warehousing: Working knowledge of Snowflake and SQL-based transformation techniques, with an understanding of modern cloud data architecture and lakehouse patterns.
• Healthcare industry experience: At least one year of experience in healthcare, preferably in revenue cycle management (RCM), with a solid understanding of healthcare billing, reimbursement, and the claims lifecycle.
• Healthcare data standards: Working knowledge of healthcare Electronic Data Interchange (EDI), particularly X12 transaction formats used for claims and remittance processing, including 837 and 835 transactions.
• Healthcare systems: Familiarity with electronic medical record systems, healthcare data integration, and the challenges associated with mapping and migrating data from different source systems.
• Cloud technologies: Familiarity with cloud platforms such as AWS or Microsoft Azure and their application to data engineering workflows.
• Data quality and troubleshooting: Ability to develop validation checks, reconcile datasets, investigate data discrepancies, and perform systematic root-cause analysis.
• Healthcare compliance: Understanding of data privacy, information security, and regulatory considerations, including HIPAA requirements for sensitive healthcare information.
• Analytical and problem-solving

  skills

  Strong attention to detail and the ability to analyze complex datasets, resolve technical issues, and develop reliable, scalable solutions.
• Communication

  skills

  Excellent written and verbal communication, with the ability to explain technical concepts and collaborate effectively with both technical and nontechnical colleagues.
• Teamwork and collaboration: A cooperative, team-oriented approach and the ability to work across engineering, implementation, product, support, and IT functions.
• Organization and time management: Ability to manage multiple onboarding tasks, maintain accurate documentation, track project milestones, and meet deadlines in a fast-paced environment.
• Adaptability and initiative: Willingness to learn new technologies, improve existing workflows, and contribute to evolving data engineering practices within a growing technology environment.

Benefits

• Competitive compensation: Annual salary ranging from $125,000 to $135,000.
• Fully remote work: Work remotely within the United States.
• Comprehensive healthcare coverage: Medical, dental, and vision insurance.
• Retirement

  benefits

  401(k) plan with employer matching contributions.
• Flexible paid time off: Unlimited vacation policy, designed to encourage employees to take time off and return refreshed.
• Learning and development: Access to an on-demand learning program to support continuous professional growth and technical skill development.
• Employee recognition: Peer-nominated awards and recognition programs that celebrate contributions and achievements.
• Team-building activities: Opportunities to participate in virtual cooking classes, yoga sessions, mixology classes, and other team activities.
• Career advancement: Opportunities to develop professionally, expand technical expertise, and pursue career growth within the organization.
• Inclusive workplace culture: A commitment to diversity, inclusion, and respect for different backgrounds, perspectives, and skills.
• Meaningful work: The opportunity to help healthcare organizations improve revenue cycle operations and compliance through reliable, data-driven technology solutions.

How Jobgether works:We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1