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Staff Data Engineer, Observability Data Lake

TX - Work from home

Pay
$118,450–236,900Pay period needs review — pay source
The typical pay range for this role is: $118,450.00 - $236,900.00 This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company’s equity award program. Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.
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Work setting
Remote — work setting source
Listed location: TX - Work from home
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Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
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What you’ll work on

Full posting

CVS Health is seeking a highly skilled Staff Data Engineer, Observability Engineering to join the Enterprise Observability Platform organization and help advance the next generation of observability, infrastructure, and security data capabilities.

  • Design and support scalable Databricks pipelines that curate observability, infrastructure, and security data

  • Develop and optimize PySpark and Structured Streaming jobs in bronze/silver/gold architectures

  • Onboard new data sources and set governance standards with Security and Infrastructure teams

  • Contribute to code reviews, CI/CD practices, and monitoring for the data platform

  • Promote best practices for Unity Catalog, Delta Lake, access controls, and cost-efficient operations

From the employer’s posting
CVS Health is seeking a highly skilled Staff Data Engineer, Observability Engineering to join the Enterprise Observability Platform organization and help advance the next generation of observability, infrastructure, and security data capabilities. The Staff Data Engineer, Observability Engineering will play a critical role in designing, building, and operating scalable data pipelines and data products that power enterprise observability, operational intelligence, and security analytics across the organization. The Staff Data Engineer, Observability Engineering is a senior individual contributor responsible for developing and optimizing Databricks-based data engineering solutions that ingest, transform, govern, and deliver high-volume telemetry, infrastructure, application, and security data. This role combines deep hands-on technical execution with ownership of engineering excellence, operational reliability, performance optimization, and data platform best practices.
Design, build, deploy, and support scalable Databricks-based data pipelines and lakehouse solutions
Develop and optimize PySpark workloads, Structured Streaming jobs, and bronze/silver/gold data architectures
Partner with Security, Infrastructure, Observability, and Platform Engineering teams to onboard new data sources, establish governance standards
Contribute to engineering standards, code reviews, CI/CD practices, monitoring strategies
promoting best practices for Databricks, Delta Lake, Unity Catalog, data governance, security controls, access management, and cost-efficient data platform operations

What you’ll bring

All qualifications

Core experience

  • 7+ years of experience building and supporting enterprise data engineering solutions using Python, Spark, PySpark, SQL, and distributed data processing technologies.
  • Bachelor’s degree from an accredited university or equivalent work experience (High School Diploma/GED plus 4 years of relevant experience).
  • 6+ years of experience designing, developing, and operating large-scale data pipelines, data ingestion frameworks, and bronze/silver/gold lakehouse architectures across multiple data sources.
  • 5+ years of experience working with Databricks in production environments, including Delta Lake, Unity Catalog, Databricks Asset Bundles, serverless SQL, performance optimization, and platform operations.
  • 4+ years of experience developing high-volume batch and streaming data solutions, implementing data quality controls, troubleshooting pipeline issues, and improving reliability, scalability, and operational efficiency.
  • 2+ years of experience collaborating with engineering teams, participating in code reviews, contributing to technical standards, applying cloud security and access management principles, and communicating technical solutions to both technical and non-technical stakeholders.

Preferred experience

  • Experience building Structured Streaming and near real-time ingestion solutions within Databricks or similar cloud-native data platforms.
  • Experience implementing Databricks governance capabilities, including Unity Catalog, storage credentials, external locations, catalog management, and access control frameworks.
  • Familiarity with OCSF or similar observability, cybersecurity, or security event normalization frameworks.
  • Experience implementing CI/CD pipelines for data engineering solutions using Databricks Asset Bundles, GitHub Actions, Azure DevOps, or equivalent automation frameworks.
Qualification wording
7+ years of experience building and supporting enterprise data engineering solutions using Python, Spark, PySpark, SQL, and distributed data processing technologies.
Bachelor’s degree from an accredited university or equivalent work experience (High School Diploma/GED plus 4 years of relevant experience).
6+ years of experience designing, developing, and operating large-scale data pipelines, data ingestion frameworks, and bronze/silver/gold lakehouse architectures across multiple data sources.
5+ years of experience working with Databricks in production environments, including Delta Lake, Unity Catalog, Databricks Asset Bundles, serverless SQL, performance optimization, and platform operations.
4+ years of experience developing high-volume batch and streaming data solutions, implementing data quality controls, troubleshooting pipeline issues, and improving reliability, scalability, and operational efficiency.
2+ years of experience collaborating with engineering teams, participating in code reviews, contributing to technical standards, applying cloud security and access management principles, and communicating technical solutions to both technical and non-technical stakeholders.
Experience building Structured Streaming and near real-time ingestion solutions within Databricks or similar cloud-native data platforms.
Experience implementing Databricks governance capabilities, including Unity Catalog, storage credentials, external locations, catalog management, and access control frameworks.
Familiarity with OCSF or similar observability, cybersecurity, or security event normalization frameworks.
Experience implementing CI/CD pipelines for data engineering solutions using Databricks Asset Bundles, GitHub Actions, Azure DevOps, or equivalent automation frameworks.
Education & alternatives
EDUCATION Bachelor’s degree from an accredited university or equivalent work experience (High School Diploma/GED plus 4 years of relevant experience). BUSINESS OVERVIEW

Tools in this posting

  • Python
  • SQL
  • Azure
  • Databricks
  • Delta Lake
  • Spark
  • PySpark
Source — Tool mentions in context
REQUIRED QUALIFICATIONS - 7+ years of experience building and supporting enterprise data engineering solutions using Python, Spark, PySpark, SQL, and distributed data processing technologies. - 6+ years of experience designing, developing, and operating large-scale data pipelines, data ingestion frameworks, and bronze/silver/gold lakehouse architectures across multiple data sources.
- 6+ years of experience designing, developing, and operating large-scale data pipelines, data ingestion frameworks, and bronze/silver/gold lakehouse architectures across multiple data sources. - 5+ years of experience working with Databricks in production environments, including Delta Lake, Unity Catalog, Databricks Asset Bundles, serverless SQL, performance optimization, and platform operations. - 4+ years of experience developing high-volume batch and streaming data solutions, implementing data quality controls, troubleshooting pipeline issues, and improving reliability, scalability, and operational efficiency.
- Familiarity with OCSF or similar observability, cybersecurity, or security event normalization frameworks. - Experience implementing CI/CD pipelines for data engineering solutions using Databricks Asset Bundles, GitHub Actions, Azure DevOps, or equivalent automation frameworks. - Prior experience supporting observability, infrastructure, cybersecurity, logging, telemetry, or operational analytics platforms in large-scale enterprise environments.
POSITION SUMMARY CVS Health is seeking a highly skilled Staff Data Engineer, Observability Engineering to join the Enterprise Observability Platform organization and help advance the next generation of observability, infrastructure, and security data capabilities. The Staff Data Engineer, Observability Engineering will play a critical role in designing, building, and operating scalable data pipelines and data products that power enterprise observability, operational intelligence, and security analytics across the organization. The Staff Data Engineer, Observability Engineering is a senior individual contributor responsible for developing and optimizing Databricks-based data engineering solutions that ingest, transform, govern, and deliver high-volume telemetry, infrastructure, application, and security data. This role combines deep hands-on technical execution with ownership of engineering excellence, operational reliability, performance optimization, and data platform best practices. Working closely with Observability Engineering, Security Engineering, Infrastructure Engineering, and Data Platform teams, the Staff Data Engineer, Observability Engineering will contribute to the evolution of the enterprise observability lakehouse by building resilient ingestion frameworks, establishing data quality standards, enhancing governance controls, and driving efficient, scalable data processing patterns. The ideal candidate is passionate about engineering high-quality solutions, proactively identifying opportunities for improvement, influencing technical standards, and raising the overall quality, reliability, and maintainability of the platform and team.
PRIMARY RESPONSIBILITIES - Design, build, deploy, and support scalable Databricks-based data pipelines and lakehouse solutions that ingest, transform, and curate observability, infrastructure, and security data from multiple enterprise sources. - Develop and optimize PySpark workloads, Structured Streaming jobs, and bronze/silver/gold data architectures while ensuring high performance, reliability, scalability, data quality, and operational excellence.
- Contribute to engineering standards, code reviews, CI/CD practices, monitoring strategies, and platform optimization efforts while proactively identifying and addressing technical debt, process gaps, and operational risks. - Support the ongoing evolution of the enterprise observability lakehouse by promoting best practices for Databricks, Delta Lake, Unity Catalog, data governance, security controls, access management, and cost-efficient data platform operations. REQUIRED QUALIFICATIONS
PREFERRED QUALIFICATIONS - Experience building Structured Streaming and near real-time ingestion solutions within Databricks or similar cloud-native data platforms. - Experience implementing Databricks governance capabilities, including Unity Catalog, storage credentials, external locations, catalog management, and access control frameworks.
- Experience building Structured Streaming and near real-time ingestion solutions within Databricks or similar cloud-native data platforms. - Experience implementing Databricks governance capabilities, including Unity Catalog, storage credentials, external locations, catalog management, and access control frameworks. - Familiarity with OCSF or similar observability, cybersecurity, or security event normalization frameworks.
- Design, build, deploy, and support scalable Databricks-based data pipelines and lakehouse solutions that ingest, transform, and curate observability, infrastructure, and security data from multiple enterprise sources. - Develop and optimize PySpark workloads, Structured Streaming jobs, and bronze/silver/gold data architectures while ensuring high performance, reliability, scalability, data quality, and operational excellence. - Partner with Security, Infrastructure, Observability, and Platform Engineering teams to onboard new data sources, establish governance standards, improve metadata management, and deliver trusted enterprise data products.

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First seen by us
Oct 15, 2026 · 14 days ago
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Last seen by us
Oct 29, 2026
Employer says posted
Sep 23, 2026

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Job description

View original posting ↗

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time.

POSITION SUMMARY

CVS Health is seeking a highly skilled Staff Data Engineer, Observability Engineering to join the Enterprise Observability Platform organization and help advance the next generation of observability, infrastructure, and security data capabilities. The Staff Data Engineer, Observability Engineering will play a critical role in designing, building, and operating scalable data pipelines and data products that power enterprise observability, operational intelligence, and security analytics across the organization. The Staff Data Engineer, Observability Engineering is a senior individual contributor responsible for developing and optimizing Databricks-based data engineering solutions that ingest, transform, govern, and deliver high-volume telemetry, infrastructure, application, and security data. This role combines deep hands-on technical execution with ownership of engineering excellence, operational reliability, performance optimization, and data platform best practices.

Working closely with Observability Engineering, Security Engineering, Infrastructure Engineering, and Data Platform teams, the Staff Data Engineer, Observability Engineering will contribute to the evolution of the enterprise observability lakehouse by building resilient ingestion frameworks, establishing data quality standards, enhancing governance controls, and driving efficient, scalable data processing patterns. The ideal candidate is passionate about engineering high-quality solutions, proactively identifying opportunities for improvement, influencing technical standards, and raising the overall quality, reliability, and maintainability of the platform and team.

 

PRIMARY RESPONSIBILITIES
  • Design, build, deploy, and support scalable Databricks-based data pipelines and lakehouse solutions that ingest, transform, and curate observability, infrastructure, and security data from multiple enterprise sources.
  • Develop and optimize PySpark workloads, Structured Streaming jobs, and bronze/silver/gold data architectures while ensuring high performance, reliability, scalability, data quality, and operational excellence.
  • Partner with Security, Infrastructure, Observability, and Platform Engineering teams to onboard new data sources, establish governance standards, improve metadata management, and deliver trusted enterprise data products.
  • Contribute to engineering standards, code reviews, CI/CD practices, monitoring strategies, and platform optimization efforts while proactively identifying and addressing technical debt, process gaps, and operational risks.
  • Support the ongoing evolution of the enterprise observability lakehouse by promoting best practices for Databricks, Delta Lake, Unity Catalog, data governance, security controls, access management, and cost-efficient data platform operations.

 

REQUIRED QUALIFICATIONS
  • 7+ years of experience building and supporting enterprise data engineering solutions using Python, Spark, PySpark, SQL, and distributed data processing technologies.
  • 6+ years of experience designing, developing, and operating large-scale data pipelines, data ingestion frameworks, and bronze/silver/gold lakehouse architectures across multiple data sources.
  • 5+ years of experience working with Databricks in production environments, including Delta Lake, Unity Catalog, Databricks Asset Bundles, serverless SQL, performance optimization, and platform operations.
  • 4+ years of experience developing high-volume batch and streaming data solutions, implementing data quality controls, troubleshooting pipeline issues, and improving reliability, scalability, and operational efficiency.
  • 2+ years of experience collaborating with engineering teams, participating in code reviews, contributing to technical standards, applying cloud security and access management principles, and communicating technical solutions to both technical and non-technical stakeholders.

 

PREFERRED QUALIFICATIONS
  • Experience building Structured Streaming and near real-time ingestion solutions within Databricks or similar cloud-native data platforms.
  • Experience implementing Databricks governance capabilities, including Unity Catalog, storage credentials, external locations, catalog management, and access control frameworks.
  • Familiarity with OCSF or similar observability, cybersecurity, or security event normalization frameworks.
  • Experience implementing CI/CD pipelines for data engineering solutions using Databricks Asset Bundles, GitHub Actions, Azure DevOps, or equivalent automation frameworks.
  • Prior experience supporting observability, infrastructure, cybersecurity, logging, telemetry, or operational analytics platforms in large-scale enterprise environments.
 EDUCATION

Bachelor’s degree from an accredited university or equivalent work experience (High School Diploma/GED plus 4 years of relevant experience).

 BUSINESS OVERVIEW

Bring your heart to CVS Health. Every one of us at CVS Health shares a single, clear purpose: Bringing our heart to every moment of your health. This purpose guides our commitment to deliver enhanced human-centric healthcare for a rapidly changing world. Anchored in our brand — with heart at its center — our purpose sends a personal message that how we deliver our services is just as important as what we deliver. Our Heart At Work Behaviors™ support this purpose. We want everyone who works at CVS Health to feel empowered by the role they play in transforming our culture and accelerating our ability to innovate and deliver solutions to make healthcare more personal, convenient, and affordable.

We strive to promote and sustain a culture of diversity, inclusion, and belonging every day. CVS Health is an affirmative action employer and is an equal opportunity employer, as are the physician-owned businesses for which CVS Health provides management services. We do not discriminate in recruiting, hiring, promotion, or any other personnel action based on race, ethnicity, color, national origin, sex/gender, sexual orientation, gender identity or expression, religion, age, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. We proudly support and encourage people with military experience (active duty, veterans, reservists, National Guard members, and military spouses) to apply for CVS Health job opportunities.

 

Pay Range

The typical pay range for this role is:

$118,450.00 - $236,900.00


This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls.  The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors.  This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above.  This position also includes an award target in the company’s equity award program. 
 

Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.

Great benefits for great people

We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families.

This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.


Additional details about available benefits are provided during the application process and on
Benefits Moments.

We anticipate the application window for this opening will close on: 10/31/2026

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.

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Pay
The typical pay range for this role is: $118,450.00 - $236,900.00 This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company’s equity award program. Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.
Location & working pattern

TX - Work from home

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