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Snowflake DBT, SQL - 13th Aug (Thursday) - Virtual Interview- Kolkata

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Onsite

Snowflake DBT, SQL - 13th Aug (Thursday) - Virtual Interview- Kolkata

Tata Consultancy Services

Snowflake DBT, SQL - 13th Aug (Thursday) - Virtual Interview- Kolkata

Skills

SQL QueriesSnowflakeGitdbt

2 months ago

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Important information


Contract type:

Permanent

Location:

Kolkata, West Bengal, India

Work mode:

Onsite

Published on:

11 August 2026

What they need


DBT (Data Build Tool), SQL, Data Modelling (Star/Snowflake schemas), Data Pipeline Development, Data Governance & Documentation, Git, CI/CD pipelines, Data Warehousing (Snowflake/BigQuery/Redshift)

  • Strong hands-on experience in DBT for developing modular and maintainable data transformation pipelines. • Proficiency in SQL and data modeling using star/snowflake schemas. • Experience integrating DBT with data warehouses such as Snowflake, BigQuery, or Redshift. • Good understanding of data governance, testing, documentation, and lineage tracking using DBT features.

Responsibility of / Expectations from the Role

1 Design and develop well-structured data models (star/snowflake schemas) using DBT.

2 Write clear and maintainable SQL-based transformation models in DBT to create clean, business-friendly datasets.

3 Implement DBT best practices including model versioning, modular development, testing, and documentation.

4 Build and maintain efficient and reliable data pipelines using DBT, integrated with data warehouses like Snowflake, BigQuery, or Redshift.

5 Monitor and optimize pipeline performance, troubleshoot data quality issues, and identify root causes.

6 Implement data testing, documentation, and lineage tracking using DBT features such as tests, docs, and sources.

7 Promote data governance practices by maintaining metadata and documentation.

8 Collaborate with data engineers and analysts to transform raw data into well-structured datasets supporting business insights.

9 Optimize and refactor DBT models for better performance and scalability.

10 Follow best practices for version control (Git), CI/CD, and data governance to ensure quality and reliability.

11 Work closely with stakeholders to understand reporting requirements and ensure data accuracy and availability

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