Snowflake DBT - 15 May - Virtual Interview - Pan India

Job description

Required Technical Skill Set: 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) Must-Have: • 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 Have • Familiarity with AWS cloud services (S3, Glue, Lambda, Step Functions). • Knowledge of Matillion, Airflow, or similar orchestration tools. • Exposure to CI/CD and version control (Git) for DBT project deployments. • Strong communication and collaboration skills with a focus on Agile delivery. SN 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.