Description

Build and optimize data pipelines on Google Cloud Platform, owning the architecture and implementation of streaming and batch processing solutions.

This role is on-site.

Responsibilities

• Develop and maintain ELT/ETL pipelines using BigQuery, GCS, Dataflow, and Pub/Sub, orchestrated via Composer or Airflow.
• Design and implement data quality, governance, and security procedures to ensure data accuracy and compliance.
• Build streaming and batch data pipelines using Python and SQL, leveraging GCP services like DataProc and Cloud Functions.
• Coach junior data engineers and contribute to solution design, IP building, and client requirement gathering.
• Implement CI/CD practices and infrastructure-as-code using Terraform and Jenkins within Agile environments.

Required Skills

• 8+ years of experience as a Data Engineer, with deep expertise in Python and SQL.
• Hands-on experience with Google Cloud Platform services: BigQuery, Dataflow, Pub/Sub, Cloud Storage, Data Fusion, and Composer/Airflow.
• Proficiency in CI/CD tools (Jenkins) and Infrastructure-as-Code (Terraform).
• Strong understanding of data warehousing architectures, data analytics, and data governance principles.
• Experience with IAM, Cloud Logging, and Monitoring for operational reliability.
• Proven ability to work in global, client-facing environments with strong communication and problem-solving skills.
• Bachelor's degree in Computer Science, Engineering, or a related field.

Preferred Skills

• Experience with AI/ML or Gen AI applications in data engineering contexts.
• Familiarity with additional ETL tools such as DBT or Talend.

Key Skills

Education

Bachelor's degree