T
Tata Consultancy Services
GCP Senior Data Engineer - S
Skills
Google Cloud PlatformSQL QueriesData EngineeringPythonJavaData AnalysisScalaCompliance
2 months ago
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Important information
Contract type:
Permanent
Salary:
₹2,500,000 – ₹4,000,000 / year
Location:
Bengaluru, Karnataka, India
Work mode:
Onsite
Published on:
28 August 2026
What they need
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL/ELT processes on Google Cloud Platform (GCP).
- Build and manage enterprise data solutions leveraging GCP services such as BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, and Composer.
- Develop batch and real-time data processing solutions to support analytics and reporting requirements.
- Design and implement data models, data warehouses, and data lakes to meet business needs.
- Collaborate with data scientists, analysts, architects, and business stakeholders to deliver data products and insights.
- Optimize data processing performance, scalability, reliability, and cost efficiency.
- Ensure data quality, governance, security, and compliance standards are followed throughout the data lifecycle.
- Automate data workflows and deployments using CI/CD and Infrastructure as Code (IaC) principles.
- Monitor and troubleshoot data pipelines, system performance, and operational issues.
- Participate in architecture discussions and contribute to cloud modernization initiatives.
- Document technical designs, operational procedures, and best practices.
Required Skills & Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, Mathematics, or a related field.
- 5+ years of experience in Data Engineering and Data Warehousing.
- 3+ years of hands-on experience with Google Cloud Platform (GCP).
- Strong expertise in SQL and data modeling concepts.
- Experience building scalable ETL/ELT pipelines and data integration solutions.
- Strong programming skills in Python, Java, or Scala.
- Hands-on experience with BigQuery and large-scale data processing technologies.
- Knowledge of streaming and batch data processing frameworks.
- Experience working with structured, semi-structured, and unstructured data.
- Understanding of Data Lake, Data Warehouse, and Lakehouse architectures.
- Familiarity with DevOps, CI/CD, and Infrastructure as Code methodologies.
- Strong analytical, troubleshooting, and problem-solving skills.
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