GCP Data Engineer

We are looking for a GCP Data Engineer to design, build, and maintain scalable data platforms on Google Cloud. The ideal candidate will have strong experience in automated data ingestion, analytics engineering, and MLOps, with the ability to support marketing analytics use cases and BI-driven decision making.

You will work closely with Data Science, Analytics, and Business teams to enable data-driven insights through robust pipelines, models, and reporting solutions.

You will:

• Design, develop, and maintain automated data ingestion pipelines on Google Cloud Platform (GCP)
• Build and optimize scalable data processing workflows using Spark / PySpark
• Support data science team, including data preparation, feature engineering, and experimentation support
• Develop, deploy, and maintain BI reporting and simulation tools using Looker
• Implement and manage MLOps pipelines for model training, deployment, monitoring, and retraining
• Write efficient, well-documented code in Python and SQL
• Ensure data quality, reliability, performance, and governance across data pipelines
• Collaborate with cross-functional teams including Data Scientists, Analysts, and Product stakeholders

• Strong hands-on experience with Google Cloud Platform (GCP)
• Experience supporting marketing analytics or attribution modeling use cases
• Familiarity with GCP services such as BigQuery, Dataflow, Dataproc, Cloud Composer, and Vertex AI
• Knowledge of CI/CD, version control, and cloud-native best practices
• Experience building automated data ingestion pipelines
• Proficiency in Python, Spark, PySpark, and SQL
• Experience developing and deploying Looker dashboards and BI solutions
• Solid understanding of data engineering concepts: ETL/ELT, data modeling, and pipeline orchestration
• Exposure to MLOps pipelines and lifecycle management of machine learning models
• Ability to work with large-scale datasets and distributed systems