Description

• Design, develop, and maintain ETL pipelines for ingesting, transforming, and delivering structured and unstructured data.
• Build and optimize data workflows using Google Cloud services such as BigQuery, Dataflow, Dataproc, and Cloud Storage.
• Implement and maintain data quality, validation, and governance frameworks across multiple data sources.
• Collaborate with data engineers, analysts, and product teams to understand data requirements and ensure alignment with business goals.
• Monitor data pipelines for performance and reliability, troubleshooting issues proactively.
• Develop and maintain technical documentation for ETL processes, architecture, and design decisions.
• Work with DevOps teams to automate deployment and manage CI/CD pipelines for data workflows.

Qualifications:

• 3–6 years of experience in ETL development, data engineering, or related fields.
• Strong proficiency with SQL and Python (or Java/Scala).
• Hands-on experience with Google Cloud Platform (GCP) — especially BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Cloud Composer.
• Experience with ETL/ELT tools such as Apache Beam, Airflow, DBT.
• Knowledge of data modeling, data lake / warehouse design, and schema optimization.
• Understanding of API integrations, streaming data, and batch processing frameworks.
• Experience with Terraform or Infrastructure as Code in GCP.
• Exposure to machine learning data pipelines or analytics engineering.
• Certification in Google Cloud Data Engineer or equivalent is a plus.
• Strong analytical and problem-solving abilities.
• Excellent communication and collaboration skills across cross-functional teams.
• Self-driven with the ability to work in fast-paced, agile environments

Key Skills

Education

Bachelor's degree