Data Engineer

Our Fortune 50 Healthcare client is seeking a Senior Data Engineer to support our mission of improving the health and well-being of our members. This role will focus on building scalable, secure, data centric solutions and compliant data platforms that power analytics, clinical insights, and business decision-making across the enterprise. The ideal candidate will have strong experience with cloud-based data platforms, Databricks, PostgreSQL , and healthcare data, with a passion for delivering high-quality, trusted data solutions in a regulated environment. Key Responsibilities Design, develop, and scalable data pipeline solutions using Databricks (Spark) and cloud-native services Build and optimize ETL/ELT workflows for ingesting structured and unstructured healthcare data (claims, clinical, provider, and member data) Develop and maintain data models in PostgreSQL and enterprise data warehouses Support Lakehouse architecture leveraging Databricks, Delta Lake , and cloud storage Improve performance, reliability, and cost-efficiency of data platforms Work with healthcare datasets, including producer/agent, broker, commission, and distribution data, ensuring proper ingestion, normalization, and optimization for analytics and reporting Ensure compliance with HIPAA, HITECH , and enterprise data governance policies Implement data security, encryption, masking, and access controls Maintain data lineage, auditability, and regulatory reporting readiness Advanced Data Processing Build real-time and batch pipelines for analytics and operational use cases Develop data transformations using PySpark and SQL within Databricks Leverage PostgreSQL for transactional and analytical workloads where applicable Integrate data from APIs, third-party vendors, and internal systems Collaboration & Stakeholder Engagement Partner with business stakeholders to support data-driven initiatives and member acquisition strategies Translate insurance distribution, agent/producer , and marketing requirements into scalable, high-quality data solutions Support downstream consumers, including Power BI, marketing analytics teams, and operational reporting stakeholders, by delivering curated, analytics-ready datasets Technical Leadership Lead design and architecture discussions for enterprise data solutions Establish and enforce best practices in data engineering, testing, and CI/CD Contribute to enterprise data strategy and platform modernization AI & Advanced Analytics (Databricks Genie) Leverage Databricks Genie (AI/BI capabilities) to enable natural language querying and democratize data access for business stakeholders Design and optimize semantic layers and governed datasets that power Genie-driven insights with trusted, high-quality data Collaborate with stakeholders to translate business questions into AI-assisted analytics workflows using Databricks Ensure AI outputs are accurate, explainable, and compliant with healthcare data governance and HIPAA requirements Leverage large language models (LLMs), including Anthropic Claude , to enhance data exploration, automate insight generation, and support conversational analytics use cases Integrate Genie capabilities with Delta Lake and curated data models to support near real-time insights and decision-making Partner with data scientists and analytics teams to enhance AI-driven use cases, including producer performance insights, marketing attribution, and member engagement analysis Required Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or related field 5–8+ years of experience in data engineering Strong programming in Python (PySpark) and advanced SQL Hands-on experience with: Databricks (core requirement) Distributed data processing frameworks (Apache Spark) Experience with cloud platforms (Azure preferred; AWS acceptable) Proficiency in building and maintaining ETL/ELT pipelines Strong understanding of data modeling and warehousing concepts Preferred Qualifications Experience in healthcare or insurance industry (payer experience strongly preferred) Familiarity with healthcare standards (e.g., FHIR, HL7 ) Experience with Delta Lake / Lakehouse architecture Knowledge of DevOps and CI/CD pipelines (Azure DevOps, GitHub Actions) Experience supporting machine learning pipelines Deep understanding of data pipelines at scale Strong experience with Databricks ecosystem and Spark optimization Expertise in PostgreSQL performance tuning and schema design Strong attention to data quality, governance, and compliance Excellent communication skills, especially with non-technical stakeholders Ability to work in a highly regulated healthcare environment Typical Technology Stack Languages: Python, SQL Version Control: Git KPIs / Success Metrics Reliability and performance of Databricks pipelines Data quality and compliance adherence (HIPAA standards) Time-to-delivery for new data products Query performance improvements in PostgreSQL and data warehouse systems J-18808-Ljbffr