Data Engineer - Kafka Connect

Role: Data Engineer - Kafka Connect

Location: Remote immediate joiner prefered.

Experience: 4+ Years

About the Role

We are seeking a skilled Data Engineer with hands-on experience in Kafka Connect and

related data ingestion tools to design and implement a Bronze Layer for our data platform. The

ideal candidate will work closely with data platform and analytics teams to build scalable and

reliable ingestion pipelines from various data sources into cloud-based storage systems.

Key Responsibilities

• Design, develop, and maintain data ingestion pipelines using Kafka Connect and

Debezium for real-time and batch data integration.

• Ingest data from MySQL and PostgreSQL databases into AWS S3, Google Cloud

Storage (GCS), and BigQuery.

• Implement best practices for data modeling, schema evolution, and efficient partitioning

in the Bronze Layer.

• Ensure reliability, scalability, and monitoring of Kafka Connect clusters and connectors.
• Collaborate with cross-functional teams to understand source systems and downstream

data requirements.

• Optimize data ingestion processes for performance and cost efficiency.
• Contribute to automation and deployment scripts using Python and cloud-native tools.
• Stay updated with emerging data lake technologies such as Apache Hudi or Apache

Iceberg.

Required Skills and Qualifications

• 2+ years of hands-on experience as a Data Engineer or similar role.
• Strong experience with Apache Kafka and Kafka Connect (sink and source

connectors).

• Experience with Debezium for change data capture (CDC) from RDBMS.
• Proficiency in working with MySQL and PostgreSQL.
• Hands-on experience with AWS S3, GCP BigQuery, and GCS.
• Proficiency in Python for automation, data handling, and scripting.
• Understanding of data lake architectures and ingestion patterns.
• Solid understanding of ETL/ELT pipelines, data quality, and observability practices.

Good to Have

• Experience with containerization (Docker, Kubernetes).
• Familiarity with workflow orchestration tools (Airflow, Dagster, etc.).
• Exposure to infrastructure-as-code tools (Terraform, CloudFormation).
• Familiarity with data versioning and table formats such as Apache Hudi or Apache

Iceberg (preferred).