Senior Data Engineer

QAT Global, a 30+ year IT consulting firm based in the US, is seeking a highly skilled

Senior Data Engineer (Kafka / CDC / AWX)

with strong English communication skills. This position will work directly with the customer located in the US and with development teams in our US, Costa Rica, and Brazil locations.

This opportunity can be 100% remote

Project Context You will be working on a

Unified Reporting Platform , responsible for capturing real-time data changes from multiple systems and publishing them to

Kafka (Amazon MSK) .

Source Systems: SQL Server (Direct) PostgreSQL (Gateway) PostgreSQL (Payments / Tokenization)

Core Stack: Debezium (CDC) Kafka (Amazon MSK – Kafka 3.x) Schema Registry AWS ECS Fargate Dead Letter Queue (DLQ)

Responsibilities: Design, configure, and maintain

Debezium connectors

(SQL Server and PostgreSQL) Ensure

reliable CDC pipelines

with low latency and high data integrity Manage

Schema Registry

and schema evolution strategies Implement and monitor

Dead Letter Queues (DLQ) Perform

testing, validation, and troubleshooting

of data pipelines Monitor pipeline performance, lag, and data consistency Collaborate with engineering teams to ensure data quality and reliability

Required Qualifications: Proven experience with

Debezium in production environments Strong understanding of

Change Data Capture (CDC)

concepts Hands-on experience with

Kafka (topics, partitions, offsets, consumers) Experience with

SQL Server CDC

and/or

PostgreSQL logical replication Familiarity with

Schema Registry and schema evolution Experience troubleshooting

data pipelines in production Ability to work in

distributed systems and cloud environments

Preferred Qualifications: Experience with

Amazon MSK Experience running workloads on

AWS (ECS, Fargate) Experience with

DLQ patterns and data validation strategies Background in

event-driven architectures

Key Technical Skills: Debezium CDC (Change Data Capture) Kafka / MSK PostgreSQL / SQL Server Schema Registry AWS

Nice to Have: Experience with high-volume, real-time data pipelines Experience with observability and monitoring (lag, throughput, failures) Experience in financial or payment systems