Job Summary :

We are seeking a highly skilled MS SQL Developer with strong expertise in database design, performance optimization, and ETL workflows, along with hands-on experience in Google Cloud Platform (GCP) services.

The ideal candidate will be responsible for developing and optimizing SQL solutions, managing data pipelines, and integrating on-premise data systems with GCP-based data environments.

Key Responsibilities :

- Design, develop, and maintain MS SQL Server databases, stored procedures, triggers, functions, and ETL workflows.

- Optimize SQL queries, indexing strategies, and overall database performance to ensure scalability and reliability.

- Implement data migration and integration between on-prem SQL servers and GCP environments.

- Work with GCP data services such as Cloud SQL, BigQuery, Cloud Storage, Dataflow, and Pub/Sub.

- Develop and maintain ETL/ELT pipelines using SQL, SSIS, or GCP-native tools.

- Perform routine database maintenance, including backups, restores, monitoring, and security management.

- Collaborate with application, analytics, and cloud engineering teams for seamless data delivery.

- Troubleshoot and resolve database and data pipeline issues in production environments.

- Document data models, architectures, and workflows for reference and governance.

Required Skills :

- Strong proficiency in MS SQL Server (T-SQL, Stored Procedures, Views, Functions).

- Proven experience in Performance Tuning, Query Optimization, and analyzing Execution Plans.

- Hands-on experience with GCP Data Services (Cloud SQL, BigQuery, Cloud Storage, Dataflow, etc.

- Working knowledge of SSIS or equivalent ETL tools.

- Solid understanding of data modeling, normalization, and schema design.

- Familiarity with version control systems (Git) and CI/CD workflows.

Nice-to-Have Skills :

- Experience with BigQuery SQL optimization.

- Knowledge of Python or Shell scripting for automation and data handling.

- Exposure to Terraform, Airflow, or similar orchestration tools.

- Understanding of Data Warehouse and Data Lake architectures.

Education : Bachelor's degree in Computer Science, Information Technology, Engineering, or related field (or equivalent experience)