Opportunity

Get Well is seeking an experienced and highly motivated Staff Data Software Engineer to help build and optimize our cloud-native data platform that powers AI, analytics, and clinical applications. You will play a key role in developing scalable, compliant data infrastructure and pipelines designed specifically for the healthcare domain, while mentoring junior engineers and leading cross-functional initiatives to drive innovation.

This is a hands-on engineering role suitable for someone who thrives at the intersection of modern data engineering, cloud-native platforms, DevOps, healthcare data, and AI enablement.  Candidates must have hands-on software development experience with at least one healthcare company—preferably in the provider space—with exposure to EHRs and core healthcare data domains.

Responsibilities

Data Engineering & Platform Development

• Design, build, and maintain scalable data pipelines supporting batch and real-time use cases.
• Develop and maintain production-grade data workflows that move and transform sensitive healthcare data across distributed systems at scale.
• Work with Spark, Databricks, Airflow/Temporal, and dbt to ingest, process, and manage structured and unstructured data.
• Design and implement reusable, efficient data models for analytics and AI/ML use cases.
• Ensure platform resiliency using CI/CD pipelines, observability tools, and logging frameworks.
• Leverage Infrastructure as Code practices using Terraform, CloudFormation, or equivalent to manage cloud resources.

Healthcare Data Integration & Compliance

• Ingest and normalize complex healthcare data sets (FHIR, HL7, CCDA, Claims, EDI, Epic/Clarity, etc.).
• Familiarity with clinical coding systems and ontologies, such as ICD-10, SNOMED CT, LOINC, or RxNorm.
• Collaborate with compliance and security teams to ensure adherence to HIPAA, GDPR, and internal controls.
• Implement fine-grained access control, encryption at rest and in transit, audit logging, and data lineage strategies.

AI & GenAI Enablement

• Work alongside AI/ML and data science teams to build pipelines feeding predictive and generative models.
• Tune data infrastructure for performance across distributed systems and hybrid data stores like SQL, MongoDB, ClickHouse.
• Prioritize scalability and flexibility in designing LLM-compatible pipelines and use GenAI best practices for healthcare use cases.
• Utilize Spark clusters and query frameworks such as SparkSQL and SPARQL for large-scale data access.
• Utilize and manage graph databases (e.g., Neo4j, Amazon Neptune, or similar) to support complex relationship modeling and healthcare data connectivity use cases.
• Enable high-quality training data pipelines and implement feature stores and model serving systems.

Data Governance, Quality & Monitoring

• Implement data quality frameworks and establish robust validation processes using tools such as Great Expectations or equivalent.
• Build automated anomaly detection tools for data drift and integrity checks.
• Support data cataloging, metadata management, and ensure consistent documentation across datasets.

Collaboration, Mentorship & Leadership

• Act as a mentor to junior engineers through code reviews, paired programming, and technical guidance.
• Lead cross-functional projects with teams including clinical informatics, architecture, security, product, and design.
• Contribute to and enforce data engineering best practices, patterns, and platform standardization.

Learning and Innovation

• Research and evaluate emerging tools and frameworks (e.g., Apache Iceberg, Delta Lake) for incorporation into the platform.
• Proactively identify opportunities to improve architecture and leverage evolving trends in GenAI and cloud-native computing.

Qualifications

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 8–12 years of experience in software or data engineering roles including at least 3 years working with large-scale or cloud-native data systems.
• Must have prior software development experience in the healthcare domain—including payers, providers, health tech, medical devices, or life sciences.
• Functional knowledge and direct experience with healthcare data types (FHIR, HL7, Claims, EDI, Epic/Clarity, etc.).
• Demonstrated experience in designing, implementing, and maintaining data pipelines that move and transform healthcare data with production-level quality, reliability, and performance.

Technical Skills

• Advanced programming experience in Python, SQL, and distributed processing with Apache Spark.
• Cloud-native platform experience with Azure.
• Proven capability with Infrastructure as Code (Terraform, CloudFormation) strongly preferred.
• Experience with data warehouses and lakes including Snowflake, Databricks, and ClickHouse.
• Familiarity working with GenAI tools and ML pipelines in production environments.
• Strong skills in data modeling, job orchestration (Airflow), data transformation (dbt), and pipeline optimization.
• Experience with DevOps/tooling stacks for CI/CD, containerization, observability, and cost optimization.
• Familiarity with data validation and anomaly detection tools such as Great Expectations.
• Experience with SparkSQL and SPARQL is a plus.

Professional Attributes

• Excellent communication and collaboration skills across cross-functional, domain, and technical stakeholders.
• Ability to lead initiatives and drive data engineering standards.
• Self-driven, with a commitment to delivering high-quality solutions in regulated and sensitive environments.

About GW RhythmX

GW RhythmX is revolutionizing healthcare through connected, AI-native intelligence that unites clinical insight, patient engagement, and system-wide care orchestration. The company combines market-leading AI precision care technology with extensive trusted patient engagement leadership to help health systems deliver the right care, at the right time, through the right clinician and channel. Its solutions are deployed across more than 150 health systems, touching more than 85M patients including 8M U.S. military veterans. The company's award-winning solutions were recognized again in 2024 by KLAS Research, Fierce Healthcare, and AVIA Marketplace. A SymphonyAI Group company, GW RhythmX leverages various firm assets, including $1B+ in R&D investment, longitudinal data related to 300 million patients, 4.4 billion total annual claims, and 1.8 million healthcare professionals at more than 3,000 facilities globally.

GW RhythmX  is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.