Senior Data Engineer, Observability Engineering

CVS Health

. Design, build, deploy, and support scalable Databricks-based data pipelines and lakehouse solutions .

Posted 9/21/2026full-timeRemote • Arizona • United StatesSenior💰 $92,700 - $222,480 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and supporting scalable Databricks-based data pipelines and lakehouse solutions, with a strong focus on data governance, quality, and operational excellence. Proficient in collaborating with cross-functional teams to optimize data ingestion and processing frameworks while ensuring security and compliance.

Highest-signal resume keywords

Databricks ExperiencePySpark DevelopmentData Pipeline DesignCI/CD ImplementationData Governance

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonSparkPySparkSQLStructured StreamingData Ingestion FrameworksDelta LakeUnity CatalogPerformance OptimizationData Quality Controls

Soft Skills

CollaborationCommunicationProblem-Solving

Tools & Technologies

Databricks Asset BundlesGitHub ActionsAzure DevOpsCloud Security PrinciplesOperational Analytics Platforms

Industry Keywords

Data EngineeringObservabilityCybersecurityOperational ExcellenceEnterprise Data Solutions

Tech Stack

Tools & technologies

AzureCloudCyber SecurityPySparkPythonSparkSQLUnity

About the role

Key responsibilities & impact

Design, build, deploy, and support scalable Databricks-based data pipelines and lakehouse solutions
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
Ensure high performance, reliability, scalability, data quality, and operational excellence
Partner with Security, Infrastructure, Observability, and Platform Engineering teams to onboard 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
Identify and address technical debt, process gaps, and operational risks
Promote best practices for Databricks, Delta Lake, Unity Catalog, data governance, security controls, access management, and cost-efficient operations

Requirements

What you’ll need

5+ years of experience building and supporting enterprise data engineering solutions using Python, Spark, PySpark, SQL, and distributed data processing technologies
5+ years of experience designing, developing, and operating large-scale data pipelines, data ingestion frameworks, and bronze/silver/gold lakehouse architectures across multiple data sources
4+ years of experience working with Databricks in production environments, including Delta Lake, Unity Catalog, Databricks Asset Bundles, serverless SQL, performance optimization, and platform operations
3+ 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
Prior experience supporting observability, infrastructure, cybersecurity, logging, telemetry, or operational analytics platforms in large-scale enterprise environments
Bachelor’s degree from an accredited university or equivalent work experience; High School Diploma/GED plus 4 years of relevant experience
Ability to work from home in Arizona

Benefits

Comp & perks

CVS Health bonus, commission or short-term incentive program in addition to base pay
Medical coverage
Dental coverage
Vision coverage
Paid time off
Retirement savings options
Wellness programs
Other resources supporting physical, emotional, and financial well-being