Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,159 postings in the last year. Stated ranges, not salaries paid.
Reads like a Data Engineer role: pipelines and data infrastructure.
Houston, TX
Live, first seen by us 31 days agoSchedule: Monday–Friday | 8:00 AM – 5:00 PM Work Location: Houston, TX / Hybrid (2-3 days a week)- Northwest Houston Corporate Headquarters Principal Data & Analytics Engineer
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 be able to reliably commute to the Houston office and meet the onsite requirements.Read the full posting
SynergenX Health Job Type: Full-Time | Exempt Schedule: Monday–Friday | 8:00 AM – 5:00 PMRead the full posting
Must be legally authorized to work in the United States
Build ETL/ELT pipelines, Databricks workflows and dimensional models
Trace and fix root causes of unexpected data discrepancies and metric changes
Add automated validation, reconciliation and anomaly alerting to pipelines
Refactor legacy pipelines and migrate workloads to standard Azure and Databricks patterns
Mentor data engineers, BI developers and analysts through code and design reviews
Develop ETL/ELT pipelines, Databricks workflows, curated datasets, dimensional models, semantic models
Trace unexpected metric changes across source systems, pipelines, transformations, and reporting layers
Implement automated validation, reconciliation, anomaly detection, monitoring, and alerting
Refactor legacy pipelines, eliminate duplicated logic, improve performance, and migrate appropriate workloads
Mentor Data Engineers, BI developers, and analysts; conduct code and design reviews
7+ years of progressive experience in data engineering, analytics engineering, BI engineering, or a related discipline.
Strong Python and/or PySpark development experience.
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.
Experience with Git, CI/CD, and modern software and data engineering practices.
Experience working with HIPAA-regulated data.
Data Modeling & Analytics
401(k) with Company Match
Experience with Databricks Lakehouse, Delta Lake, and Unity Catalog.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,159 postings in the last year. Stated ranges, not salaries paid.
Day 31
Similar jobs usually come down between day 6 and day 54.
From 11,573 similar postings that came down. Coming down is not always a hire.
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Own complex data solutions from start to finish. Lead discovery, requirements gathering, architecture, development, testing, deployment, documentation, monitoring, and production support. - Build production data pipelines and analytical products. Develop ETL/ELT pipelines, Databricks workflows, curated datasets, dimensional models, semantic models, and integrations using SQL, Python/PySpark, Azure Data Factory, and Databricks. - Turn business processes into reliable data logic. Partner with Operations, Finance, Pharmacy, Clinical Operations, Marketing, and other teams to understand their workflows and create consistent data definitions and solutions.
- 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.
- SQL - Python - PySpark
- Demonstrated success independently delivering 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.
Programming & Integrations - SQL - Python
Build the Data Foundation Behind a Growing Healthcare Leader At SynergenX Health, technology and data help us improve patient care, strengthen operations, and make better business decisions. As one of the nation’s leading hormone optimization and wellness organizations, we’re investing in modern Azure and Databricks solutions to support our continued growth. We’re looking for an experienced Principal Data & Analytics Engineer who enjoys solving complex problems, working directly with business stakeholders, and building reliable data solutions from discovery through production.
- Build quality and monitoring into every solution. Implement automated validation, reconciliation, anomaly detection, monitoring, and alerting to identify pipeline failures, data drift, and unexpected historical changes. - Modernize existing data solutions. Refactor legacy pipelines, eliminate duplicated logic, improve performance, and migrate appropriate workloads to standardized Azure and Databricks patterns. - Strengthen the analytics layer. Develop and optimize datasets and semantic models that support consistent metrics and trustworthy historical reporting.
- Strong hands-on experience with Databricks and Apache Spark. - Strong Microsoft Azure experience, particularly Azure Data Factory and Azure data services. - Strong data modeling skills, including dimensional models, star schemas, and analytical data models.
- API integration experience. - Experience with Azure DevOps. - Experience modernizing legacy data warehouses or pipelines.
Data Engineering & Processing - Azure Data Factory - Azure Databricks
- Azure Data Factory - Azure Databricks - Apache Spark
Cloud & Governance - Microsoft Azure Data Services - Microsoft Fabric — Preferred
- Technical Documentation - Azure DevOps — Preferred Why Join SynergenX?
- Strong Python and/or PySpark development experience. - Strong hands-on experience with Databricks and Apache Spark. - Strong Microsoft Azure experience, particularly Azure Data Factory and Azure data services.
- Microsoft Fabric experience. - Experience with Databricks Lakehouse, Delta Lake, and Unity Catalog. - API integration experience.
- Experience integrating operational and transactional systems with analytics platforms. - Databricks Data Engineer certification. - Microsoft Fabric or Power BI certification.
- ETL/ELT Pipelines - Databricks Workflows - Data Integration
Your work will help teams trust their data, understand performance, and make decisions that support patient care and business growth. You’ll have the opportunity to solve challenging problems across multiple business functions, modernize important data systems, and influence how we build and maintain our enterprise data platform. From investigating an unexpected financial metric to designing a scalable Databricks pipeline, you’ll bring both technical depth and business understanding to the solution. If you enjoy taking ownership, working through ambiguity, and building data products that people depend on, we’d love to hear from you.
- Data Integration - Delta Lake / Lakehouse Architecture — Preferred Programming & Integrations
- Investigate difficult data discrepancies. Trace unexpected metric changes across source systems, pipelines, transformations, and reporting layers. Identify root causes and implement lasting fixes. - Understand the downstream impact of changes. Evaluate how updates to shared datasets and business logic affect Power BI reports, KPIs, financial calculations, operational workflows, and dependent systems. - Build quality and monitoring into every solution. Implement automated validation, reconciliation, anomaly detection, monitoring, and alerting to identify pipeline failures, data drift, and unexpected historical changes.
- 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.
- Databricks Data Engineer certification. - Microsoft Fabric or Power BI certification. - Experience supporting AI/ML or automation workloads.
- Curated Analytical Datasets - Microsoft Power BI - Semantic Models
- Azure Databricks - Apache Spark - ETL/ELT Pipelines
- Python - PySpark - APIs and Enterprise System Integrations
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New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
SynergenX Health
Job Type: Full-Time | Exempt
Schedule: Monday–Friday | 8:00 AM – 5:00 PM
Work Location: Houston, TX / Hybrid (2-3 days a week)- Northwest Houston Corporate Headquarters
Principal Data & Analytics EngineerBuild the Data Foundation Behind a Growing Healthcare Leader
At SynergenX Health, technology and data help us improve patient care, strengthen operations, and make better business decisions. As one of the nation’s leading hormone optimization and wellness organizations, we’re investing in modern Azure and Databricks solutions to support our continued growth.
We’re looking for an experienced Principal Data & Analytics Engineer who enjoys solving complex problems, working directly with business stakeholders, and building reliable data solutions from discovery through production.
This is a senior, hands-on individual contributor role that combines data engineering, analytics engineering, solution architecture, and business problem solving. You’ll personally investigate, design, build, test, deploy, and monitor solutions while serving as a senior technical resource for our Data & AI team.
Reports to: Senior Manager, Data & AI
Role Type: Senior Individual Contributor
Location: Houston, TX
Work Arrangement: Hybrid — 2–3 days per week onsite
Own complex data solutions from start to finish. Lead discovery, requirements gathering, architecture, development, testing, deployment, documentation, monitoring, and production support.
Build production data pipelines and analytical products. Develop ETL/ELT pipelines, Databricks workflows, curated datasets, dimensional models, semantic models, and integrations using SQL, Python/PySpark, Azure Data Factory, and Databricks.
Turn business processes into reliable data logic. Partner with Operations, Finance, Pharmacy, Clinical Operations, Marketing, and other teams to understand their workflows and create consistent data definitions and solutions.
Investigate difficult data discrepancies. Trace unexpected metric changes across source systems, pipelines, transformations, and reporting layers. Identify root causes and implement lasting fixes.
Understand the downstream impact of changes. Evaluate how updates to shared datasets and business logic affect Power BI reports, KPIs, financial calculations, operational workflows, and dependent systems.
Build quality and monitoring into every solution. Implement automated validation, reconciliation, anomaly detection, monitoring, and alerting to identify pipeline failures, data drift, and unexpected historical changes.
Modernize existing data solutions. Refactor legacy pipelines, eliminate duplicated logic, improve performance, and migrate appropriate workloads to standardized Azure and Databricks patterns.
Strengthen the analytics layer. Develop and optimize datasets and semantic models that support consistent metrics and trustworthy historical reporting.
Improve engineering practices. Help establish practical standards for Git, CI/CD, testing, documentation, reusable development patterns, data lineage, and deployment.
Serve as a senior technical partner. Mentor Data Engineers, BI developers, and analysts; conduct code and design reviews; and help resolve challenging technical issues.
Integrate enterprise source systems. Evaluate databases, APIs, SaaS platforms, EHR and pharmacy systems, financial applications, and other sources to determine appropriate ingestion strategies.
Support Data & AI initiatives. Build dependable data foundations and integrations for automation, AI/ML, and advanced analytics.
7+ years of progressive experience in data engineering, analytics engineering, BI engineering, or a related discipline.
Demonstrated success independently delivering 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, particularly 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.
Demonstrated 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.
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.
Candidates should bring strong experience with the core technologies below, along with exposure to relevant supporting tools.
Azure Data Factory
Azure Databricks
Apache Spark
ETL/ELT Pipelines
Databricks Workflows
Data Integration
Delta Lake / Lakehouse Architecture — Preferred
SQL
Python
PySpark
APIs and Enterprise System Integrations
Dimensional Modeling
Star Schemas
Curated Analytical Datasets
Microsoft Power BI
Semantic Models
DAX
Consistent KPI and Metric Definitions
Microsoft Azure Data Services
Microsoft Fabric — Preferred
Unity Catalog — Preferred
Data Lineage
Data Quality Validation
Monitoring and Alerting
Git
CI/CD
Automated Testing
Code and Design Reviews
Technical Documentation
Azure DevOps — Preferred
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
Hybrid work arrangement in Houston
Opportunity to influence enterprise data architecture and engineering standards
Meaningful projects supporting clinical, pharmacy, financial, and operational teams
A growing healthcare organization investing in its data and technology capabilities
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 be able to reliably commute to the Houston office and meet the onsite requirements.
As a senior individual contributor, you’ll remain actively involved in production development while providing technical guidance, mentoring teammates, and helping shape solution design.
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.
Your work will help teams trust their data, understand performance, and make decisions that support patient care and business growth.
You’ll have the opportunity to solve challenging problems across multiple business functions, modernize important data systems, and influence how we build and maintain our enterprise data platform. From investigating an unexpected financial metric to designing a scalable Databricks pipeline, you’ll bring both technical depth and business understanding to the solution.
If you enjoy taking ownership, working through ambiguity, and building data products that people depend on, we’d love to hear from you.
SynergenX Health is an Equal Opportunity Employer. We are committed to an inclusive workplace and make employment decisions based on qualifications, merit, and business needs. We consider all qualified applicants without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, disability, genetic information, protected veteran status, or any other status protected by applicable federal, state, or local law.
Please do not email the company or company representatives directly. Applications must be submitted through this posting to be considered.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
Houston, TX
Schedule: Monday–Friday | 8:00 AM – 5:00 PM Work Location: Houston, TX / Hybrid (2-3 days a week)- Northwest Houston Corporate Headquarters Principal Data & Analytics Engineer
This is a senior, hands-on individual contributor role that combines data engineering, analytics engineering, solution architecture, and business problem solving. You’ll personally investigate, design, build, test, deploy, and monitor solutions while serving as a senior technical resource for our Data & AI team. Reports to: Senior Manager, Data & AI Role Type: Senior Individual Contributor Location: Houston, TX Work Arrangement: Hybrid — 2–3 days per week onsite What You’ll Do
More relevant text appears in the full description.
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.