Principal Data & Analytics Engineer

Key Responsibilities: Own complex data solutions from discovery and requirements gathering through architecture, development, testing, deployment, documentation, monitoring, and production support. Build production data pipelines and analytical products, including ETL/ELT pipelines, Databricks workflows, curated datasets, dimensional models, semantic models, and integrations using SQL, Python/PySpark, Azure Data Factory, and Databricks. Translate business processes into dependable data logic by partnering with Operations, Finance, Pharmacy, Clinical Operations, Marketing, and other teams to define consistent data and deliver solutions. Investigate difficult data discrepancies by tracing unexpected metric changes across source systems, pipelines, transformations, and reporting layers, then implementing lasting fixes. Assess downstream impact when shared datasets and business logic change, including effects on Power BI reports, KPIs, financial calculations, operational workflows, and dependent systems. Embed quality and monitoring in every solution through automated validation, reconciliation, anomaly detection, monitoring, and alerting for pipeline failures, data drift, and unexpected historical changes. Modernize existing data solutions by refactoring legacy pipelines, removing duplicated logic, improving performance, and migrating appropriate workloads to standardized Azure and Databricks patterns. Strengthen the analytics layer by developing and optimizing datasets and semantic models for consistent metrics and trustworthy historical reporting. Improve engineering practices by helping establish standards for Git, CI/CD, testing, documentation, reusable development patterns, data lineage, and deployment. Act as a senior technical partner by mentoring Data Engineers, BI developers, and analysts, and by conducting code and design reviews to resolve challenging technical issues. Integrate enterprise source systems by evaluating databases, APIs, SaaS platforms, EHR and pharmacy systems, financial applications, and other sources to determine ingestion strategies. Support Data & AI initiatives by building dependable data foundations and integrations that enable automation, AI/ML, and advanced analytics.

Preferred Qualifications: Healthcare, pharmacy, EHR, or other regulated-data experience. Experience working with HIPAA-regulated data. Microsoft Fabric experience. Experience with Databricks Lakehouse, Delta Lake, and Unity Catalog. API integration experience. Experience with Azure DevOps. Experience modernizing legacy data warehouses or pipelines. Experience integrating operational and transactional systems with analytics platforms. Databricks Data Engineer certification. Microsoft Fabric or Power BI certification. Experience supporting AI/ML or automation workloads. Work Environment This is a hybrid position based in Houston, Texas, with 2–3 days per week onsite for collaboration with the Data & AI team and business stakeholders. Candidates must reliably commute to the Houston office and meet the onsite requirements. As a senior individual contributor, you will remain actively involved in production development while providing technical guidance, mentoring teammates, and helping shape solution design. Employment Requirements Must be legally authorized to work in the United States. SynergenX Health is unable to provide current or future employment visa sponsorship for this position. Successful completion of all pre-employment screening requirements.

Location: Houston, TX (hybrid)

Compensation: USD 150,000 per yearly

Experience: 7+ years