Sr. Data Engineer, Onboarding

7Seventy; United States; Remote; USD 140,000 - 150,000; Full time

Job summary

7Seventy is seeking a Sr. Data Engineer, Onboarding to design, develop, and maintain scalable data pipelines that ingest healthcare data into a cloud analytics platform.

The role focuses on ETL/ELT development, data ingestion, transformation, legacy system migration, and automation to enhance onboarding efficiency, data quality, and reliability. The engineer will work with Databricks, PySpark, Python, Snowflake, and advanced SQL to process healthcare claims, remittance advice, and EMR data,

Qualifications

• 8+ years of professional experience in data engineering, ETL/ELT pipeline development, and data warehousing.
• 3+ years of programming using Python and advanced SQL.
• 2+ years hands-on Databricks experience including Delta Lake, notebooks, jobs, workflows.
• Practical experience with Snowflake data modeling, SQL transformations, and data warehouse processes.
• 2+ years of healthcare industry experience with billing, claims processing, and the revenue cycle.
• Experience with cloud infrastructure on AWS or Microsoft Azure.
• Experience with SaaS applications and healthcare revenue cycle processes.

Responsibilities

• Design, build, optimize, and maintain scalable ETL/ELT data pipelines using Databricks, PySpark, and Python.
• Develop healthcare data ingestion and transformation workflows for X12 837I/P/D claims, 835 remittance, and EMR data.
• Parse, normalize, validate, and map datasets to the platform's data model for reliable analytics.
• Design and optimize Snowflake data models and SQL transformations to support reporting and analytics.
• Migrate data from legacy systems (e.g., SQL Server) to the cloud platform.
• Build reusable frameworks and automated workflows to reduce onboarding tasks.
• Implement automated data validation and reconciliation to maintain data integrity.
• Monitor data feeds and pipelines post-implementation to improve reliability and cost efficiency.
• Integrate EMR data from Epic, Cerner, Meditech, and Athenahealth with claims data.

Skills

ETL/ELT pipelines

Data warehousing

Healthcare data integration

Python

SQL

Education

Bachelor's degree in Computer Science, Data Science, Health Informatics, Information Systems, or related field

Tools

Databricks

PySpark

Snowflake

Delta Lake

Cloud (AWS/Azure)

Job description

Experience: 8+ years in data engineering, ETL/ELT, and data warehousing

Core Areas: Data Engineering, ETL/ELT Pipelines, Databricks, PySpark, Python, Snowflake, Healthcare Data Integration, Data Warehousing

Compensation: $140,000–$150,000

About the Role

The Sr. Data Engineer, Onboarding is responsible for designing, developing, and maintaining scalable data pipelines that integrate customer healthcare data into a cloud-based analytics and operational platform. This hands-on engineering position focuses on ETL/ELT development, healthcare data ingestion, data transformation, legacy system migration, and automation that improves customer onboarding efficiency, data quality, and processing reliability.

The role uses Databricks, PySpark, Python, Snowflake, and advanced SQL to process healthcare claims, remittance advice, and electronic medical record (EMR) data. Responsibilities include supporting healthcare revenue cycle management (RCM) and compliance workflows, collaborating with Implementation, Product, Support, and IT teams, resolving complex data integration issues, and mentoring junior engineers.

What You'll Do

• Design, build, optimize, and maintain scalable ETL/ELT data pipelines using Databricks, PySpark, and Python, following Bronze, Silver, and Gold lakehouse architecture patterns.
• Develop healthcare data ingestion and transformation workflows for X12 837I/P/D institutional, professional, and dental claims, 835 electronic remittance advice, and EMR data.
• Parse, normalize, validate, and map customer healthcare datasets to the platform's data model, ensuring accurate and reliable downstream analytics and operational processing.
• Design and optimize Snowflake data models, SQL transformations, and data warehousing processes to support reporting, analytics, and data accessibility.
• Convert, migrate, and integrate data from legacy databases and systems, including Microsoft SQL Server, into the modern cloud data platform.
• Build reusable Python, PySpark, and SQL frameworks, engineering utilities, and automated workflows that reduce manual onboarding tasks and improve processing efficiency.
• Implement automated data validation, quality checks, reconciliation processes, and discrepancy resolution to maintain accuracy and data integrity.
• Monitor and troubleshoot customer data feeds, ingestion pipelines, and file processing workflows after implementation, using operational metrics to identify reliability, performance, automation, and cost optimization opportunities.
• Integrate and validate EMR data from systems such as Epic, Cerner, Meditech, and Athenahealth alongside claims data to enable comprehensive healthcare reporting.
• Partner with Implementation, Product, Support, and IT teams to define data requirements, clarify mapping specifications, coordinate delivery priorities, and support customer onboarding.
• Investigate and resolve escalated data ingestion, transformation, and integration issues through root-cause analysis and durable engineering fixes.
• Track onboarding deliverables using project management platforms such as Monday.com, identify risks early, and communicate progress to internal stakeholders.
• Maintain clear technical documentation covering data pipelines, transformation logic, data flows, operational procedures, and runbooks.
• Coordinate the transition of completed onboarding workflows to Support teams, providing the documentation required for ongoing operations and troubleshooting.
• Mentor less experienced data engineers, conduct code reviews, and share engineering practices and technical knowledge.
• Maintain appropriate data security, regulatory compliance, and information integrity standards, including HIPAA requirements.
• Perform additional related responsibilities as needed.

Qualifications

Required Experience

• 8+ years of professional experience in data engineering, ETL/ELT pipeline development, and data warehousing.
• 3+ years of programming experience using Python and advanced SQL.
• 2+ years of hands‑on experience with Databricks, including Delta Lake, notebooks, jobs, workflows, and PySpark.
• Practical experience with Snowflake, including data modeling, SQL transformations, and data warehouse processes.
• 2+ years of experience in the healthcare industry, with a solid understanding of healthcare billing, claims processing, reimbursement models, and the revenue cycle.
• Experience working with cloud infrastructure and data services on AWS or Microsoft Azure.
• Experience working with SaaS applications and healthcare revenue cycle processes.

Required Skills

• Strong technical capabilities in designing, developing, maintaining, and troubleshooting ETL/ELT pipelines and cloud-based data processing workflows.
• Hands‑on proficiency with Python, PySpark, Databricks, Snowflake, and advanced SQL for data ingestion, transformation, modeling, and automation.
• Working knowledge of Databricks Delta Lake architecture, notebook development, scheduled jobs, and workflow orchestration.
• Ability to develop and optimize SQL-based data models, warehouse transformations, and reliable data processing solutions.
• Understanding of healthcare revenue cycle management (RCM), including billing processes, the claims lifecycle, and reimbursement.
• Working knowledge of healthcare EDI (X12) transactions, including 837 claims and 835 remittance data used in billing and payment processing.
• Ability to ingest, transform, map, and validate healthcare claims and electronic medical record data across integrated systems.
• Knowledge of EMR data integration requirements and healthcare platforms such as Epic, Cerner, Meditech, and Athenahealth.
• Ability to identify and resolve data quality issues through automated validation, reconciliation, monitoring, and root‑cause analysis.
• Understanding of data integrity, security practices, and HIPAA‑related regulatory requirements.
• Strong analytical, problem‑solving, and troubleshooting skills with close attention to technical detail.
• Effective written and verbal communication with technical and non‑technical colleagues.
• Collaborative working style and the ability to manage engineering responsibilities in a fast‑paced environment.

Education

• Bachelor's degree in Computer Science, Data Science, Health Informatics, Information Systems, or a related field, or equivalent professional experience.

Preferred Qualifications

• Healthcare industry experience specifically involving revenue cycle management (RCM).
• Medical, dental, and vision insurance coverage.
• 401(k) retirement plan with company matching contributions.
• Unlimited vacation policy.
• Professional development, career advancement, and on-demand learning opportunities.
• Peer-nominated employee awards and recognition programs.
• Remote employee activities, including virtual cooking classes, yoga sessions, and mixology classes.