Principal Data & Analytics Engineer

SynergenX Health Holdings LLC seeks a hands-on Principal Data & Analytics Engineer to design and deliver end-to-end, production data solutions. This senior individual contributor role is based in Houston, Texas (hybrid) and focuses on building reliable data pipelines and analytics capabilities using Azure and Databricks.

• 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.

• 7+ years of progressive experience in data engineering, analytics engineering, BI engineering, or a related discipline.
• Proven ability to deliver complex data solutions independently, from initial requirements through production.
• Advanced SQL skills, including development, optimization, and troubleshooting of complex data transformations.
• Strong hands-on experience with Databricks and Apache Spark.
• Strong Python and/or PySpark development experience.
• 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 sufficient 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.

• 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, Unity Catalog
• Microsoft Azure Data Services, Microsoft Fabric
• Git, CI/CD, Azure Dev Ops, APIs, EHR

• 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…