Description
We're building a world of health around every individual , shaping a more connected, convenient and compassionate health experience.
As a Senior Data Engineer - PostgreSQL and MongoDB, you 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.
Responsibilities
- 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.
Requirements
- 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.
Benefits
- Medical, dental, and vision coverage
- Paid time off
- Retirement savings options
- Wellness programs
- Other resources, based on eligibility