Data Architecture &

- Design: Define and design enterprise-grade, scalable, and secure data architectures leveraging Snowflake and DBT, aligned with business and analytics requirements. 
- Data Pipeline Development: Build, optimize, and maintain ETL/ELT pipelines for data ingestion, transformation, and loading from multiple structured and unstructured data sources. 
- DBT Model Development: Develop, test, and document DBT models; establish modular, version-controlled, and reusable transformation logic to ensure data consistency and quality. 
- Data Modeling: Design and implement dimensional, relational, and d Snowflake compute resources, and data storage to achieve scalability and cost efficiency. 
- Data Governance &
- Quality: Implement best practices for data validation, lineage tracking, and schema evolution using DBT testing frameworks and Snowflake features. 
- Collaboration &
- Stakeholder Management: Partner with data architects, analysts, and business teams to ensure the delivery of analytics-ready abreast of emerging technologies and tools in the up-to-date data stack (e.g., Airflow, Fivetran, Snowpipe, DataOps) and drive continuous innovation.

Required Skills &

- Qualifications



Education: Bachelor’s or Master’s degree in Computer Science,



Information Technology, Data Engineering, or a related field. 

Experience: 10–15 years of overall experience in data engineering, with at least 3–5 years of hands-on experience in Snowflake and DBT. 

- Technical Expertise: o Snowflake: Deep understanding of Snowflake architecture — virtual warehouses, micro-partitioning, clustering, query optimization, data sharing, and security. o DBT: Expertise in DBT model building, macros, Jinja scripting, testing, and documentation. o SQL: Advanced SQL skills for data wrangling, analysis, and performance tuning. o ETL/ELT Tools: Experience with modern ingestion/orchestration tools (Airflow, Fivetran, Matillion, Azure Data Factory, or AWS Glue). o Programming Languages: Strong knowledge of Python or Scala for data processing and automation. o Cloud Platforms: Hands-on experience in AWS, Azure, or GCP (Snowflake integrations, data pipelines, and security best practices). o Version Control &
- DevOps: Proficiency in Git, CI/CD, and code-based deployment practices. o Data Governance: Familiarity with metadata management, lineage tracking, and compliance (e.g., GDPR, HIPAA).

📌 Architect (Chennai)
🏢 Virtusa
📍 Chennai