Required Skills
Robust experience in Python programming.
Hands-on expertise with PySpark for large-scale data processing.
Experience with Google Cloud Platform (GCP) services:
BigQuery
Dataproc
Dataflow
Cloud Storage
Pub/Sub
Cloud Composer (Airflow)
Robust SQL skills and experience with relational databases.
Experience building batch and real-time data pipelines.
Positive understanding of Data Lake and Data Warehouse concepts.
Knowledge of distributed computing and Spark optimization techniques.
Experience with Git, CI/CD pipelines, and Agile methodologies.

referred Skills
Experience with Kafka and streaming architectures.
Knowledge of Terraform or Infrastructure as Code (IaC).
Experience with Docker and Kubernetes.
Understanding of data modeling and dimensional modeling concepts.
Exposure to machine learning data pipelines.

Key Responsibilities
Design, develop, and maintain scalable ETL/ELT pipelines using PySpark and Python.
Build and manage data processing solutions on Google Cloud Platform (GCP).




Develop data ingestion frameworks from structured, semi-structured, and unstructured data sources.
Implement data transformation, cleansing, and aggregation processes for analytics and reporting.
Work with BigQuery, Cloud Storage, Dataproc, Dataflow, Pub/Sub, Composer (Airflow), and other GCP services.
Optimize PySpark jobs for performance, scalability, and cost efficiency.
Collaborate with Data Scientists, Analysts, and Application teams to deliver high-quality data solutions.
Ensure data quality, governance, security, and compliance standards are met.
Troubleshoot and resolve production data issues and performance bottlenecks.
Participate in code reviews, CI/CD implementation, and DevOps practices.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Gcp Data Engineer Bengaluru
🏢 Zensar
📍 Bengaluru