Project – the aim you’ll have

Our customer provides innovative solutions and insights that enable our clients to manage risk and hire the best talent. Their advanced global technology platform supports fully scalable, configurable screening programs that meet the unique needs of over 33,000 clients worldwide. Headquartered in Atlanta, GA, they have an internationally distributed workforce spanning 19 countries with about 5,500 employees. Our partner perform over 93 million screens annually in over 200 countries and territories.

Position – how you’ll contribute

• Build and operate change-data-capture pipelines from PostgreSQL into Azure, using Kafka Connect and Debezium as the core of the platform
• Configure, deploy and scale connectors end to end - connector setup, task management, offsets, schema history, and snapshot strategy
• Run these pipelines as stateful workloads on Kubernetes (AKS), covering configuration, secrets, networking and resource tuning
• Monitor and troubleshoot the platform in production: connector failures, task rebalances, restarts, throughput and backpressure, message-size limits, retries and recovery
• Automate the platform in Python - configuration-driven onboarding of new data sources, pipeline orchestration, monitoring and alerting, recovery workflows, and automated testing
• Integrate CDC streams with the wider Azure data stack: Event Hubs, ADLS, Azure PostgreSQL, ADF and Databricks
• Manage platform infrastructure as code, so environments are reproducible and changes are reviewable
• Apply data protection requirements to sensitive data flowing through the pipelines - masking, hashing, access control and retention

Expectations – the experience you need

• Solid commercial experience as a data or platform engineer, with hands-on work on streaming or CDC pipelines rather than batch reporting alone
• Practical Kafka knowledge - topics, partitions, offsets, consumer groups and delivery semantics - including at least one Kafka Connect deployment you ran yourself
• Strong SQL and PostgreSQL skills, with working knowledge of WAL, logical replication, replication slots and replication lag
• Working understanding of CDC concepts: initial snapshots, inserts, updates and deletes, event ordering, at-least-once delivery, and schema evolution
• Confident Python for automation and tooling - orchestration, monitoring, recovery scripts, and automated tests
• Hands-on experience with Azure data services, for example Event Hubs, ADLS or Azure PostgreSQL
• Comfortable working with Kubernetes as a user: deploying workloads, handling configuration and secrets, reading logs, debugging failing pods