Description

What You'll Do:

• Design, develop, and maintain scalable data pipelines using Google Cloud Platform (GCP) services.
• Build, optimize, and manage BigQuery data models to support analytical and reporting workloads.
• Develop ETL/ELT processes and data ingestion frameworks for structured, semi-structured, and unstructured data.
• Integrate data from multiple enterprise applications and source systems into a centralized cloud data platform.
• Design and optimize complex SQL queries for data transformation, analytics, and reporting.
• Develop and maintain dashboards and reporting solutions using Looker Studio.
• Monitor data workflows and improve performance through effective schema design, partitioning, clustering, and workload optimization.
• Implement data quality frameworks, validation processes, and monitoring mechanisms.
• Establish and support metadata management, data governance, and lineage tracking processes.
• Utilize Python for data processing, automation, scripting, and API integrations.
• Collaborate with business users, analysts, architects, and engineering teams to understand and implement data requirements.
• Troubleshoot and resolve data-related issues while ensuring availability, reliability, and performance of data platforms.
• Support data platform modernization and continuous improvement initiatives.
• Maintain technical documentation, operational procedures, and engineering best practices.

Expertise You'll Bring:

• 5?8 years of experience in Data Engineering with strong exposure to Google Cloud Platform.
• Hands-on experience with BigQuery, including schema design, query optimization, partitioning, clustering, and performance tuning.
• Strong proficiency in SQL for advanced data transformation, analytics, and reporting.
• Solid programming experience in Python for data engineering, automation, and integration development.
• Experience with GCP services such as Cloud Storage, Pub/Sub, Cloud Functions, and Cloud Monitoring.
• Strong understanding of ETL/ELT methodologies and large-scale data processing frameworks.
• Experience integrating APIs and enterprise source systems into cloud-based data platforms.
• Knowledge of data governance, metadata management, data lineage, and data quality frameworks.
• Experience building and supporting cloud-native analytics and reporting platforms.
• Familiarity with Looker Studio or similar BI and data visualization tools.
• Understanding of dimensional modeling, data warehousing concepts, and analytics solutions.
• Exposure to machine learning workflows and data engineering support for AI/ML initiatives is preferred.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent communication and stakeholder management abilities.
• Ability to work effectively in Agile and collaborative team environments.
• Self-driven mindset with a strong focus on innovation, quality, and continuous improvement

Key Skills

Education

Any Graduate