Data Engineer

Role Overview

We are looking for a Data Engineer to design, build, and maintain scalable data pipelines and cloud-based data platforms. In this role, you will work with modern data engineering tools and Google Cloud technologies to support data integration, processing, and analytics across the organization.

You will collaborate with data scientists, analysts, and software engineers to ensure reliable data delivery, efficient data processing, and high-quality data solutions that support business and analytical needs.

Key Responsibilities

• Design, develop, and maintain data pipelines and ETL/ELT workflows.

• Build and optimize data processing solutions using Python and SQL.

• Develop and maintain integrations with external systems using REST APIs.

• Work with Google Cloud Platform (GCP) services such as BigQuery, GKE, and Dataproc.

• Manage infrastructure and environments using Infrastructure as Code (Terraform).

• Implement and maintain CI/CD pipelines using GitHub Actions.

• Ensure secure data access and governance using IAM and VPC Service Controls (VPC-SC).

• Collaborate with cross-functional teams in an Agile development environment.

• Monitor and optimize data workflows to ensure reliability and performance.

Required Skills

• Experience with Python for data processing and pipeline development.

• Strong knowledge of SQL and relational data systems.

• Experience building and maintaining ETL/ELT data pipelines.

• Experience integrating systems using REST APIs.

• Hands-on experience with Google Cloud Platform, particularly:

  • BigQuery

  • GKE

  • Dataproc

• Experience with Infrastructure as Code (Terraform).

• Knowledge of CI/CD tools, especially GitHub Actions.

• Understanding of cloud security concepts, including IAM and VPC-SC.

• Experience working in Agile environments.

• Strong communication skills and English proficiency at C1 level.

Nice to Have

• Experience with containerized environments and Kubernetes ecosystems.

• Familiarity with data governance and cloud security best practices.

• Experience supporting analytics or machine learning data pipelines.