Principal Data & Analytics Engineer

SynergenX Health is hiring a senior, hands-on Principal Data & Analytics Engineer to build end-to-end production data solutions using Azure and Databricks in a Houston, TX (hybrid) role.

Responsibilities

• Own complex data solutions end to end: discovery, requirements gathering, architecture, development, testing, deployment, documentation, monitoring, and production support.
• Build production data pipelines and analytical products using SQL, Python/PySpark, Azure Data Factory, and Databricks.
• Create ETL/ELT pipelines, Databricks workflows, curated datasets, dimensional models, semantic models, and downstream integrations.
• Translate business processes into reliable data logic by partnering with Operations, Finance, Pharmacy, Clinical Operations, Marketing, and other stakeholders.
• Investigate difficult data discrepancies by tracing unexpected metric changes across source systems, pipelines, transformations, and reporting layers to identify root cause and implement durable fixes.
• Assess downstream impact of changes across Power BI reports, KPIs, financial calculations, operational workflows, and dependent systems.
• Build quality and monitoring into every solution with 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 workloads to standardized Azure and Databricks patterns.
• Strengthen the analytics layer by developing and optimizing datasets and semantic models that support 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: mentor Data Engineers, BI developers, and analysts; lead code and design reviews; help 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 strategy.
• Support Data & AI initiatives by building dependable data foundations and integrations for automation, AI/ML, and advanced analytics.

Requirements

• 7+ years of progressive experience in data engineering, analytics engineering, BI engineering, or a related discipline.
• Proven ability to independently deliver complex data solutions from initial requirements through production.
• Advanced SQL skills, including developing, optimizing, and troubleshooting complex data transformations.
• Strong Python and/or PySpark development experience.
• Strong hands-on experience with Databricks and Apache Spark.
• Strong Microsoft Azure experience, especially Azure Data Factory and Azure data services.
• Strong data modeling skills including dimensional models, star schemas, and analytical data models.
• Experience building and supporting production ETL/ELT pipelines.
• Experience implementing automated data quality validation, monitoring, and production alerting.
• Working knowledge of Power BI architecture, semantic models, and DAX to evaluate downstream analytical impacts.
• Experience with Git, CI/CD, and modern software and data engineering practices.
• Ability to troubleshoot complex data discrepancies across multiple systems.
• Ability to investigate source systems, understand business processes, and deliver solutions when requirements are initially ambiguous.
• Ability to work directly with nontechnical stakeholders and translate business needs into technical solutions.
• Strong written documentation and verbal communication skills.

Technologies

• Azure Data Factory
• Azure Databricks
• Apache Spark
• SQL
• Python
• PySpark
• Databricks Workflows
• ETL/ELT Pipelines
• Microsoft Power BI
• DAX
• Dimensional Modeling
• Star Schemas
• Semantic Models
• Delta Lake
• Lakehouse Architecture
• Microsoft Azure Data Services
• Microsoft Fabric
• Unity Catalog
• Git
• CI/CD
• Azure DevOps
• APIs
• EHR

Benefits

• Medical, Dental, and Vision Insurance
• 401(k) with Company Match
• Paid Time Off and Paid Holidays
• Company-Paid Life Insurance
• Short- and Long-Term Disability
• Employee Assistance Program
• Professional development opportunities

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

• Hybrid role based in Houston, Texas (2–3 days per week onsite) for collaboration with the Data & AI team and business stakeholders.
• Candidates must be able to reliably commute to the Houston office and meet onsite requirements.
• As a senior individual contributor, you will remain actively involved in production development while providing technical guidance, mentoring teammates, and shaping 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.