Hire Databricks Expert

Hire a Databricks Senior Developer - Data Engineering & Clinical Analytics

Description

At TechVariable, we bring deep expertise in leveraging Databricks to accelerate digital transformation in U.S. healthcare. Our specialized team of engineers works closely with healthcare organizations—spanning patients, payers, and providers—to build secure, scalable, and compliant data solutions. From streamlining clinical data pipelines to enabling real-time analytics for value-based care, HEDIS, eCQM, and FHIR interoperability, we empower our partners to unlock insights, improve outcomes, and optimize operational efficiency. With a contractor-based delivery model and a focus on HIPAA-compliant, Data Normalization Pipelines for HL7 v2, FHIR, CDA, X12, CCD, C-CDA feeds, we help healthcare innovators harness the full power of Databricks to advance population health and care intelligence. The TechVariable R&D Business Technology team serves as a strategic IT partner to U.S. healthcare organizations, delivering innovative Databricks-powered solutions that drive transformative, value-based care. We enable our clients to advance population health analytics, clinical informatics, and global health development through secure, scalable data architectures. With deep expertise in FHIR, HEDIS, and eCQM standards, we help teams unlock real-time insights, improve agility, and future-proof their data platforms—positioning them to lead in a rapidly evolving healthcare landscape.

Expertise

Engineering Leadership & Expertise

Lead the design and execution of scalable, secure data architectures using Databricks and modern data engineering practices tailored for healthcare.
Provide hands-on technical guidance to resolve complex challenges in data pipelines, analytics, and platform performance.
Mentor engineering teams through collaborative problem-solving, code reviews, and best practice adoption to foster continuous growth and innovation.

Databricks-Driven Healthcare Data Solutions

Architect and build clinical and operational data workflows on Databricks, leveraging Apache Spark to transform high-volume datasets for use in outcomes research, risk stratification, and care optimization.
Develop and manage Delta Lake-based data assets to support longitudinal patient views, quality reporting, and regulatory submissions, ensuring optimal performance and scalability.
Create reusable Databricks notebooks for advanced analytics, cohort analysis, and predictive modeling, adhering to best practices in documentation, compliance, and reproducibility.

Performance Tuning & Optimization

Monitor ETL pipelines for efficiency and accuracy, implementing optimizations to accelerate real-time clinical event processing and minimize resource overhead.
Continuously refine Spark job configurations and query logic to enhance throughput across high-demand use cases like claims analytics, care gap detection, and population segmentation.
Design cluster usage strategies that balance cost-efficiency and compute performance for regulated healthcare workloads.

Platform Reliability & Operations

Maintain robust Databricks environments tailored for HIPAA-compliant use, managing cluster orchestration, autoscaling, and workload isolation.
Troubleshoot and resolve pipeline failures and environment issues in collaboration with SRE and DevOps teams, ensuring high availability and seamless CI/CD integration.
Proactively enforce data governance and access controls across projects to ensure auditability and patient data security.

Cross-Functional Collaboration

Partner with clinical data managers, epidemiologists, real-world evidence (RWE) analysts, and informatics teams to translate medical research goals into actionable data pipelines and insights.
Serve as a liaison between engineering and non-technical stakeholders, simplifying technical complexity while maintaining alignment with clinical, operational, and business objectives.

Development & Scalable Engineering Solutions

Contribute to the development and optimization of robust data pipelines and orchestration workflows on Databricks, aligned with clinical and operational healthcare data needs.
Lead code reviews, enforce data engineering best practices, and facilitate technical design discussions to drive continuous improvement and engineering excellence.
Ensure end-to-end testing and deployment pipelines with automated validation frameworks to maintain data accuracy, integrity, and regulatory compliance.
Transition MVPs and proof-of-concept analytics pipelines into secure, production-grade environments, designed for maintainability and high availability.

Clinical Data Engineering & Oversight

Apply in-depth knowledge of clinical data domains—including eCRF, lab results, IVRS, and SDTM structures—to build intelligent, efficient, and auditable data flows.
Maintain and scale data review and monitoring platforms that support clinical operations, pharmacovigilance, and regulatory reporting with high reliability and responsiveness.
Collaborate with clinical informatics and data governance teams to oversee data migrations from legacy EDC and CTMS systems, ensuring traceability and compliance with CDISC and GCP standards.
Continuously address technical debt and identify architectural improvements to support evolving clinical data requirements and long-term system scalability.

Databricks Senior Developer - Data Engineering & Clinical Analytics

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