Staff Data Engineer

CVS Health

. Lead the design and implementation of a near real-time transactional cache platform supporting APIs, applications, and digital experiences .

Posted 9/28/2026full-timeRemote • United StatesLead💰 $106,605 - $260,590 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing enterprise-scale data platforms, focusing on PostgreSQL and MongoDB optimization, CDC pipelines, and operational data architecture. Proven ability to lead technical initiatives, mentor engineering teams, and ensure platform reliability and performance in production environments.

Highest-signal resume keywords

Data EngineeringPostgreSQL OptimizationMongoDB Data ModelingChange Data Capture (CDC)Cloud Platform Services (GCP)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Python DevelopmentSQL DevelopmentETL/ELT Pipeline DevelopmentSchema DesignIndexing StrategiesQuery OptimizationOperational Data Store DesignTransactional Cache ArchitectureEvent-Driven ArchitectureInfrastructure as Code (Terraform)

Soft Skills

Technical LeadershipCommunicationMentoring

Tools & Technologies

UniVerseWIntegrateUnix/LinuxGCP ServicesKafkaPub/SubGKE/KubernetesCloud SQLDataproc ServerlessCloud Composer (Airflow)

Certifications & Qualifications

Cloud Certifications (AWS/GCP)

Industry Keywords

HealthcareAgileSAFeDistributed SystemsMicroservices

Tech Stack

Tools & technologies

AirflowAWSCloudDistributed SystemsETLGoogle Cloud PlatformKafkaKubernetesLinuxMicroservicesMongoDBPostgresPythonSDLCSQLTerraformUnix

About the role

Key responsibilities & impact

Lead the design and implementation of a near real-time transactional cache platform supporting APIs, applications, and digital experiences
Design and support CDC pipelines replicating data from UniVerse into PostgreSQL using vendor-supported replication technologies
Develop and maintain transformation pipelines converting operational relational data into optimized MongoDB document structures
Design and evolve MongoDB document models, indexing strategies, partitioning approaches, and query patterns for high-throughput, low-latency API consumption
Partner with API and application development teams to define and deliver cache-ready domain models
Establish data freshness, latency, monitoring, and availability standards
Optimize PostgreSQL and MongoDB performance through schema design, indexing, query tuning, and capacity planning
Own platform reliability, observability, troubleshooting, incident response, and operational support for production environments
Develop operational runbooks, monitoring dashboards, alerting strategies, and support procedures
Provide technical leadership across engineering teams and drive architecture and modernization initiatives
Mentor engineers and establish engineering standards for CDC, operational data pipelines, and cloud-native data platforms

Requirements

What you’ll need

7+ years of data engineering, software engineering, or data platform development experience
5+ years designing and implementing enterprise-scale data platforms and distributed systems
Experience with UniVerse or UniData operational databases
Proficiency in PICK BASIC, wIntegrate, Unix/Linux, and SDLC methodologies
Strong experience with Change Data Capture (CDC), replication technologies, and near real-time data movement patterns
Experience designing operational data stores, transactional caches, or API-serving data platforms
Strong Python and SQL development skills
Experience developing and supporting production ETL/ELT pipelines
Experience with Linux/Unix environments
Ability to troubleshoot distributed data processing and data synchronization issues
Strong architecture, communication, and technical leadership skills
Experience with GCP services including Cloud SQL, Dataproc Serverless, Cloud Composer (Airflow), Monitoring, IAM, and cloud networking fundamentals
PostgreSQL expertise including schema design, query optimization, indexing, performance tuning, and high availability concepts
MongoDB Atlas expertise including data modeling, aggregation frameworks, index design, and performance optimization
Experience implementing transactional cache or operational data platform architectures
Kafka, Pub/Sub, or event-driven architecture experience
Experience building data platforms that support APIs and microservices
Terraform or Infrastructure as Code experience
Experience with GKE/Kubernetes
Experience designing highly available and low-latency data platforms
Agile/SAFe experience in large enterprises
Healthcare experience
Cloud certifications (AWS/GCP) preferred

Benefits

Comp & perks

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