Sr. 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 Sr. Data Engineer, Onboarding based in the United States. Overview We are seeking an experienced Senior Data Engineer to design, build, and optimize scalable data pipelines that support healthcare revenue cycle management and compliance initiatives. In this fully remote role, you will lead complex data onboarding projects, transforming healthcare claims, remittance, and electronic medical record (EMR) data into reliable, actionable information. You will work with a modern cloud data stack, including Databricks, PySpark, Python, and Snowflake, to develop robust data engineering solutions. Your expertise will help automate processes, improve data quality, and accelerate customer implementations. You will collaborate with cross-functional teams to solve technical challenges and deliver efficient, secure, and scalable data integrations. Additionally, you will mentor junior engineers, establish best practices, and drive continuous improvements across the data onboarding lifecycle. This is an opportunity to combine advanced engineering expertise with meaningful contributions to healthcare technology.

Design and optimize data pipelines: Build, maintain, and scale ETL/ELT pipelines using Databricks, PySpark, and Python, following a Bronze/Silver/Gold lakehouse architecture. Lead healthcare data onboarding: Ingest, parse, transform, and map healthcare claims data, including 837I/P/D transactions, 835 remittance advice, and EMR records, into the appropriate data models. Develop data warehouse solutions: Build and optimize Snowflake data models, SQL transformations, and data warehousing processes to support reliable reporting and analytics. Manage data migration: Lead the conversion and migration of data from legacy systems, including Microsoft SQL Server, into modern cloud-based data platforms. Drive automation and efficiency: Develop reusable frameworks, tools, and automated workflows that reduce manual effort, improve data accessibility, and enhance pipeline performance and cost efficiency. Ensure data quality and reliability: Implement validation checks, reconciliation processes, and monitoring solutions to identify discrepancies and maintain accurate, consistent data feeds. Integrate healthcare systems: Connect and validate EMR data from platforms such as Epic, Cerner, Meditech, and Athenahealth with claims data to enable comprehensive reporting. Resolve complex technical issues: Investigate ingestion and integration failures, perform root-cause analysis, implement permanent fixes, and address escalations promptly. Collaborate across teams: Partner with Implementation, Product, Support, and IT stakeholders to define requirements, establish data mappings, prioritize deliverables, and maintain project timelines. Provide technical leadership: Mentor junior engineers, conduct code reviews, share technical knowledge, and promote engineering standards and best practices. Manage documentation and handoffs: Maintain technical documentation, data flow diagrams, pipeline specifications, and operational runbooks to support ongoing maintenance and smooth transitions to Support teams. Maintain security and compliance: Follow HIPAA and other applicable regulatory requirements while safeguarding healthcare data and preserving its integrity. Support continuous improvement: Track project progress, communicate risks, provide regular stakeholder updates, and identify opportunities to improve data engineering processes and operational outcomes. Requirements Education: Bachelor's degree in Computer Science, Data Science, Health Informatics, Information Systems, or a related discipline, or equivalent professional experience. Professional experience: At least 8 years of experience in data engineering, ETL/ELT development, and data warehousing. Programming expertise: At least 3 years of hands-on experience with Python and advanced SQL for data transformation, automation, and analytics. Databricks and PySpark: At least 2 years of practical experience with Databricks, including Delta Lake, notebooks, jobs, and workflows, alongside strong PySpark skills. Snowflake: Working experience with Snowflake, including data modeling, SQL transformations, and warehouse optimization. Healthcare industry knowledge: At least 2 years of healthcare experience, preferably in revenue cycle management (RCM), with a solid understanding of medical billing, claims processing, and reimbursement models. Healthcare data standards: Working knowledge of healthcare EDI and X12 transaction formats, particularly 837 claims and 835 remittance transactions. Cloud platforms: Experience with cloud environments such as AWS or Microsoft Azure. Data engineering best practices: Ability to develop scalable pipelines, implement automated data quality controls, troubleshoot complex integrations, and optimize data processing workflows. Analytical and problem-solving skills: Strong attention to detail and the ability to identify data inconsistencies, investigate root causes, and deliver effective technical solutions. Communication and collaboration: Excellent written and verbal communication skills, with the ability to work effectively with both technical and non-technical stakeholders. Leadership and mentoring: Demonstrated ability to guide less experienced engineers, review code, share knowledge, and influence technical decisions. Project management: Ability to manage multiple priorities, communicate progress and risks proactively, and deliver high-quality work in a fast-paced environment. Security awareness: Understanding of healthcare data privacy, HIPAA requirements, and secure data handling practices. Benefits Competitive salary: Annual compensation ranging from $140,000 to $150,000 . Fully remote work: Work remotely from the United States. Comprehensive healthcare coverage: Medical, dental, and vision insurance. Retirement savings: 401(k) plan with an employer match. Unlimited paid time off: Flexible vacation policy designed to support rest and work-life balance. Professional development: Access to on-demand learning resources, career advancement opportunities, and continuous learning initiatives. Inclusive workplace: A commitment to diversity, equity, inclusion, and a culture that values different backgrounds and perspectives. Employee recognition: Peer-nominated awards and recognition programs that celebrate individual and team contributions. Remote team activities: Opportunities to participate in virtual cooking classes, yoga sessions, and other team-building activities. Meaningful impact: The opportunity to improve healthcare data infrastructure and support revenue cycle and compliance operations for healthcare organizations nationwide.