Key Responsibilities
- Design and implement modern data engineering solutions on Google Cloud Platform.
- Develop and maintain scalable batch and real-time data processing pipelines.
- Build cloud-based data lakes and modern data warehouse solutions.
- Create and maintain optimal data pipeline architecture using GCP services.
- Work with:
- BigQuery
- Dataflow
- Dataproc
- Cloud Storage
- Data Fusion
- Airflow
- Drive data platform modernization and transformation initiatives.
- Perform assessment and analysis of legacy data platforms and define modernization roadmaps.
- Implement process improvements for:
- Data ingestion
- ETL processing
- Data delivery
- Platform scalability
- Develop extraction, transformation, and loading solutions using Python and PySpark.
- Support CI/CD implementation for data engineering deployments.
- Define and monitor KPIs for platform modernization initiatives.
- Collaborate with business, product, analytics, and engineering teams.

Must-Have Skills

Google Cloud Platform




- Strong hands-on experience with:
- BigQuery
- Cloud Storage (GCS)
- Dataflow
- Dataproc
- Data Fusion
- Airflow
- Experience working on cloud-native data platforms.

Data Engineering
- Strong understanding of:
- Data Warehousing
- Data Lakes
- Data Platform Modernization
- ETL/ELT Frameworks

Programming
- Robust expertise in:
- Python
- PySpark
- SQL

Big Data
- Experience building:
- Batch processing solutions
- Real-time data pipelines
- Knowledge of Spark-based distributed data processing.

DevOps & Automation
- Exposure to:
- CI/CD Pipelines
- Release Automation
- Monitoring & Logging Frameworks

Operating Systems
- Strong knowledge of:
- Linux

Good-to-Have Skills
- Experience with:
- Hadoop
- Hive
- Kafka
- Apache Beam
- Sqoop
- Exposure to:
- On-Premise to Cloud migrations
- Enterprise Data Modernization programs

📌 GCP Data Engineer (Bengaluru)
🏢 Tata Consultancy Services
📍 Bengaluru