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Senior Data Engineer - PostgreSQL and MongoDB

NY - Work from hom

Pay
$92,700–203,940/yearAnnual period assumed — pay source
The typical pay range for this role is: $92,700.00 - $203,940.00 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.
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Work setting
Not stated
Employment
Full-time — employment source
Time Type Full time Pay Range
Employment type in the employer’s posting: Full time
From the employer’s posting
Apply at CVS Health

What you’ll work on

Full posting

Senior Data Engineer - PostgreSQL and MongoDB will design, build, and support a near real-time transactional cache platform that enables APIs, digital experiences, and downstream services to consume operational data outside of the legacy UniVerse environment.

The ideal candidate will possess strong expertise in operational data platforms, CDC technologies, data replication, PostgreSQL, MongoDB, and cloud-native data engineering.

  • Build and maintain CDC pipelines replicating UniVerse data into PostgreSQL

  • Convert relational operational data into optimized MongoDB document structures

  • Tune MongoDB and PostgreSQL indexing, schema, and query performance

  • Troubleshoot production issues and take part in incident response and root cause analysis

  • Partner with API teams to define cache-ready domain models

From the employer’s posting
Senior Data Engineer - PostgreSQL and MongoDB will design, build, and support a near real-time transactional cache platform that enables APIs, digital experiences, and downstream services to consume operational data outside of the legacy UniVerse environment. This role is responsible for developing and supporting data flows from UniVerse through CDC replication into PostgreSQL, transformation and enrichment processes on GCP, and delivery of optimized data models within MongoDB Atlas.
The ideal candidate will possess strong expertise in operational data platforms, CDC technologies, data replication, PostgreSQL, MongoDB, and cloud-native data engineering. This individual will contribute to the design, implementation, performance optimization, reliability, and operational support of the transactional cache ecosystem. The platform is intended to reduce transactional workloads on UniVerse while providing scalable, near real-time access for APIs and services.
Build and maintain Change Data Capture (CDC) pipelines that replicate data from UniVerse into PostgreSQL
Develop and support transformation pipelines that convert operational relational data into optimized MongoDB document structures.
Optimize PostgreSQL and MongoDB performance through schema design, indexing, query tuning, and capacity planning.
Troubleshoot production issues and participate in operational support, incident response, and root cause analysis activities.
Partner with API and application development teams to define and deliver cache-ready domain models

What you’ll bring

All qualifications

Core experience

  • 5+ years of data engineering, software engineering, or data platform development experience.
  • Bachelor’s degree, or equivalent experience (HS diploma + 4 years relevant experience)
  • 3+ years designing, developing, and supporting enterprise-scale data platforms and distributed systems.
  • Experience with Change Data Capture (CDC), replication technologies, and near real-time data movement patterns.
  • Experience designing and supporting operational data stores, transactional caches, or API-serving data platforms.
  • Strong Python and SQL development skills.

Preferred experience

  • Experience implementing transactional cache or operational data platform architectures.
  • Experience building data platforms that support APIs and microservices.
  • Experience with GKE/Kubernetes.
  • Experience designing highly available and low-latency data platforms.
Qualification wording
5+ years of data engineering, software engineering, or data platform development experience.
Bachelor’s degree, or equivalent experience (HS diploma + 4 years relevant experience)
3+ years designing, developing, and supporting enterprise-scale data platforms and distributed systems.
Experience with Change Data Capture (CDC), replication technologies, and near real-time data movement patterns.
Experience designing and supporting operational data stores, transactional caches, or API-serving data platforms.
Strong Python and SQL development skills.
Experience implementing transactional cache or operational data platform architectures.
Experience building data platforms that support APIs and microservices.
Experience with GKE/Kubernetes.
Experience designing highly available and low-latency data platforms.
Education & alternatives
Education Bachelor’s degree, or equivalent experience (HS diploma + 4 years relevant experience) Anticipated Weekly Hours

Tools in this posting

  • Python
  • SQL
  • AWS
  • GCP
  • Kafka
  • Kubernetes
  • MongoDB
  • PostgreSQL
  • Terraform
  • Airflow
Source — Tool mentions in context
- Experience designing and supporting operational data stores, transactional caches, or API-serving data platforms. - Strong Python and SQL development skills. - Experience with GCP services including Cloud SQL, Dataproc Serverless, Cloud Composer (Airflow), Monitoring, IAM, and cloud networking fundamentals.
- Strong Python and SQL development skills. - Experience with GCP services including Cloud SQL, Dataproc Serverless, Cloud Composer (Airflow), Monitoring, IAM, and cloud networking fundamentals. - Experience developing and supporting production ETL/ELT pipelines.
- Healthcare industry experience. - AWS experience. - Cloud certifications (AWS and/or GCP) preferred.
- AWS experience. - Cloud certifications (AWS and/or GCP) preferred. - EST coast hours preferred
- 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.
Position Summary Senior Data Engineer - PostgreSQL and MongoDB will design, build, and support a near real-time transactional cache platform that enables APIs, digital experiences, and downstream services to consume operational data outside of the legacy UniVerse environment. This role is responsible for developing and supporting data flows from UniVerse through CDC replication into PostgreSQL, transformation and enrichment processes on GCP, and delivery of optimized data models within MongoDB Atlas. The ideal candidate will possess strong expertise in operational data platforms, CDC technologies, data replication, PostgreSQL, MongoDB, and cloud-native data engineering. This individual will contribute to the design, implementation, performance optimization, reliability, and operational support of the transactional cache ecosystem. The platform is intended to reduce transactional workloads on UniVerse while providing scalable, near real-time access for APIs and services.
Senior Data Engineer - PostgreSQL and MongoDB will design, build, and support a near real-time transactional cache platform that enables APIs, digital experiences, and downstream services to consume operational data outside of the legacy UniVerse environment. This role is responsible for developing and supporting data flows from UniVerse through CDC replication into PostgreSQL, transformation and enrichment processes on GCP, and delivery of optimized data models within MongoDB Atlas. The ideal candidate will possess strong expertise in operational data platforms, CDC technologies, data replication, PostgreSQL, MongoDB, and cloud-native data engineering. This individual will contribute to the design, implementation, performance optimization, reliability, and operational support of the transactional cache ecosystem. The platform is intended to reduce transactional workloads on UniVerse while providing scalable, near real-time access for APIs and services. What You Will Do
- Build and maintain Change Data Capture (CDC) pipelines that replicate data from UniVerse into PostgreSQL using vendor-supported replication technologies. - Develop and support transformation pipelines that convert operational relational data into optimized MongoDB document structures. - Implement and support MongoDB document models, indexing strategies, partitioning approaches, and query patterns to support high-throughput, low-latency API consumption.
- Develop and support transformation pipelines that convert operational relational data into optimized MongoDB document structures. - Implement and support MongoDB document models, indexing strategies, partitioning approaches, and query patterns to support high-throughput, low-latency API consumption. - Partner with API and application development teams to define and deliver cache-ready domain models that meet performance and scalability requirements.
- Monitor and improve data freshness, latency, availability, and reliability of transactional cache workloads. - Optimize PostgreSQL and MongoDB performance through schema design, indexing, query tuning, and capacity planning. - Troubleshoot production issues and participate in operational support, incident response, and root cause analysis activities.
- 3+ years designing, developing, and supporting enterprise-scale data platforms and distributed systems. - Strong MongoDB Atlas /PostgreSQL experience including data modeling, aggregation frameworks, index design, and performance optimization. - Experience with Change Data Capture (CDC), replication technologies, and near real-time data movement patterns.
- Design, develop, and support a near real-time transactional cache platform supporting APIs, applications, and digital experiences. - Build and maintain Change Data Capture (CDC) pipelines that replicate data from UniVerse into PostgreSQL using vendor-supported replication technologies. - Develop and support transformation pipelines that convert operational relational data into optimized MongoDB document structures.
- Experience building data platforms that support APIs and microservices. - Terraform or Infrastructure as Code experience. - Experience with GKE/Kubernetes.

Posting record

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Status in our records
Live
First seen by us
Oct 15, 2026 · 14 days ago
Recorded sightings
23
Last seen by us
Oct 29, 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

Senior Data Engineer - PostgreSQL and MongoDB will design, build, and support a near real-time transactional cache platform that enables APIs, digital experiences, and downstream services to consume operational data outside of the legacy UniVerse environment. This role is responsible for developing and supporting data flows from UniVerse through CDC replication into PostgreSQL, transformation and enrichment processes on GCP, and delivery of optimized data models within MongoDB Atlas.


The ideal candidate will possess strong expertise in operational data platforms, CDC technologies, data replication, PostgreSQL, MongoDB, and cloud-native data engineering. This individual will contribute to the design, implementation, performance optimization, reliability, and operational support of the transactional cache ecosystem. The platform is intended to reduce transactional workloads on UniVerse while providing scalable, near real-time access for APIs and services.


What You Will Do

  • Design, develop, and support a near real-time transactional cache platform supporting APIs, applications, and digital experiences.
  • Build and maintain Change Data Capture (CDC) pipelines that replicate data from UniVerse into PostgreSQL using vendor-supported replication technologies.
  • Develop and support transformation pipelines that convert operational relational data into optimized MongoDB document structures.
  • Implement and support MongoDB document models, indexing strategies, partitioning approaches, and query patterns to support high-throughput, low-latency API consumption.
  • Partner with API and application development teams to define and deliver cache-ready domain models that meet performance and scalability requirements.
  • Monitor and improve data freshness, latency, availability, and reliability of transactional cache workloads.
  • Optimize PostgreSQL and MongoDB performance through schema design, indexing, query tuning, and capacity planning.
  • Troubleshoot production issues and participate in operational support, incident response, and root cause analysis activities.
  • Develop and maintain operational runbooks, monitoring dashboards, alerting strategies, and support procedures.
  • Collaborate with architects, senior engineers, and cross-functional teams to implement scalable and maintainable data platform solutions.
  • Contribute to engineering best practices, code reviews, documentation, and continuous improvement initiatives.
  • Mentor junior engineers and share knowledge related to CDC, data pipelines, and cloud-native data engineering practices.

Required Qualifications

  • 5+ years of data engineering, software engineering, or data platform development experience.
  • 3+ years designing, developing, and supporting enterprise-scale data platforms and distributed systems.
  • Strong MongoDB Atlas /PostgreSQL experience including data modeling, aggregation frameworks, index design, and performance optimization.
  • Experience with Change Data Capture (CDC), replication technologies, and near real-time data movement patterns.
  • Experience designing and supporting operational data stores, transactional caches, or API-serving data platforms.
  • Strong Python and SQL development skills.
  • Experience with GCP services including Cloud SQL, Dataproc Serverless, Cloud Composer (Airflow), Monitoring, IAM, and cloud networking fundamentals.
  • Experience developing and supporting production ETL/ELT pipelines.
  • Experience working in Linux/Unix environments.
  • Ability to troubleshoot distributed data processing and data synchronization issues.
  • Strong problem-solving, communication, and collaboration skills.

Preferred Qualifications

  • 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 industry experience.
  • AWS experience.
  • Cloud certifications (AWS and/or GCP) preferred.
  • EST coast hours preferred


Education

Bachelor’s degree, or equivalent experience (HS diploma + 4 years relevant experience)

Anticipated Weekly Hours

40

Time Type

Full time

Pay Range

The typical pay range for this role is:

$92,700.00 - $203,940.00

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. 
 

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.

Source details

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Pay
The typical pay range for this role is: $92,700.00 - $203,940.00 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.
Location & working pattern

NY - Work from hom

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