Associate Process Manager

We are looking for an experienced GCP Data Engineer to design, develop, and maintain scalable data pipelines and ETL/ELT frameworks on the Google Cloud Platform.

The candidate will work extensively with BigQuery, Python/PySpark, Airflow/Cloud Composer, and Google Cloud Storage to process and transform large volumes of campaign, customer, and clickstream data.

The ideal candidate should have strong hands-on experience in data engineering, excellent SQL and Python skills, and a good understanding of cloud-based data pipeline architecture.

The role will involve building reliable production pipelines, optimizing BigQuery performance and costs, implementing automation, and supporting critical data workflows.

• Design, develop, and maintain scalable and reliable data pipelines on GCP.
• Build batch and, where required, near-real-time data ingestion and transformation pipelines.
• Develop robust ETL/ELT frameworks for large volumes of structured and semi-structured data.
• Ingest data from multiple sources into Google Cloud Storage and BigQuery.
• Develop reusable and modular data engineering components.
• Implement appropriate error handling, retry mechanisms, logging, and data validation.

• 4–8 years of experience in Data Engineering.
• Strong hands-on experience with GCP.
• Strong proficiency in SQL, preferably extensive experience with BigQuery SQL.
• Strong hands-on experience in Python and/or PySpark.
• Experience developing ETL/ELT data pipelines.
• Hands-on experience with BigQuery.
• Hands-on experience with Google Cloud Storage (GCS).
• Experience with Apache Airflow / Cloud Composer.
• Good understanding of data pipeline architecture and data engineering best practices.
• Experience with Git and CI/CD practices.
• Exposure to Jenkins or similar CI/CD tools.
• Experience in production support, monitoring, troubleshooting, and performance optimization.

Good to Have

• Experience working with campaign, marketing, customer, or clickstream data.
• Experience with large-scale data processing.
• Knowledge of Dataflow / Apache Beam.
• Knowledge of Pub/Sub and event-driven architectures.
• Experience with real-time or streaming data pipelines.
• Knowledge of data warehousing and dimensional data modeling.
• Experience with data quality frameworks and validation.
• Knowledge of GCP IAM and security concepts.
• Experience with Cloud Monitoring / Logging.
• Experience working in Agile/Scrum environments.

The ideal candidate should:

• Have strong hands-on technical expertise rather than only theoretical knowledge.
• Be comfortable writing complex SQL and Python/PySpark code.
• Have experience independently designing and developing data pipelines.
• Understand how to build scalable and cost-efficient solutions on GCP.
• Be capable of troubleshooting production issues and taking ownership until resolution.
• Have good analytical and problem-solving skills.
• Be comfortable working with multiple stakeholders and managing delivery timelines.
• Demonstrate good communication and documentation skills.