Data Engineer

nuevaDesde Argentina

Remoto desde Argentina
Tiempo completo
Remoto
Senior
5+ años de experiencia

Requisitos

python
sql
aws
gcp
docker
kubernetes
terraform
kafka
airflow
bigquery

• 5+ años de experiencia
• inglés intermedio o más (el aviso está escrito en inglés)

La búsqueda

At TechBiz Global , we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking an Data Engineer to join one of our clients ' teams. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you.

Requirements

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:

• 5+ 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

Originally posted on Himalayas

Publicado en Himalayas. Los datos de requisitos los extrae Maru del aviso: ante cualquier duda, manda el aviso original.