Senior Data Platform Engineer (CDC)

Quick Facts

Senior Data Platform Engineer (CDC)

Description

Design and build a next-generation data platform that enables engineering teams to publish, discover, govern, and reuse data products at scale. Develop CDC-based data publishing/consumption services using PostgreSQL, Debezium, Kafka, and DataHub, and implement GitOps-driven workflows for data contracts and schema governance. Drive platform reliability, observability, lineage, and governance practices while creating internal tools that improve developer self-service.

Responsibilities

• Design and build a next-generation Data Platform for organization-wide engineering use
• Develop data publishing and consumption services (PostgreSQL, Debezium CDC, Kafka, DataHub)
• Create GitOps-driven workflows for data contracts, schema governance, ownership, and lifecycle management
• Build internal tools and automation to improve developer experience and enable self-service data products
• Collaborate with Product, Platform, Data Engineering, Analytics, and AI/ML teams to define and implement data standards
• Drive platform reliability, observability, lineage, and governance practices

Requirements

• Strong software engineering experience in backend, platform, infrastructure, or other data-intensive environments
• Solid understanding of distributed systems, event-driven architectures, and scalability challenges
• Hands-on experience with PostgreSQL (or other relational databases)
• Hands-on experience with Kafka and CDC tools such as Debezium (or similar streaming technologies)
• Hands-on experience with Kubernetes and cloud-native environments
• Experience building platforms, internal tooling, automation, CI/CD pipelines, or developer-facing services
• Ability to work through ambiguity, make architectural decisions, and deliver production-ready solutions
• Strong English communication skills

Benefits

• Opportunity to shape a platform from the ground up rather than maintain existing pipelines
• Influence how data products are published, governed, and consumed across the organization
• Collaborate with engineering, analytics, infrastructure, and AI/ML teams