• 
  

  • Design, develop, and maintain scalable data pipelines using Snowflake.

  • Build and optimize ELT workflows using dbt.

  • Develop and orchestrate data pipelines using Apache Airflow.

  • Design and implement efficient data models to support analytical and business reporting

  requirements.

  • Perform data ingestion from multiple structured and semi-structured data sources.

  • Optimize Snowflake performance through query tuning, clustering, partitioning, and warehouse

  optimization.

  • Develop reusable, scalable, and maintainable SQL transformations.

  • Implement data quality checks, validation, and monitoring processes.

  • Collaborate with Data Architects, Business Analysts, BI Developers, and cross-functional teams to

  deliver robust data solutions.

  • Troubleshoot production issues and ensure high availability of data pipelines.

  • Follow best practices for version control, CI/CD, testing, and documentation.

Desired Candidate Profile

• 8+ years of experience in Data Engineering.

• Strong hands-on experience with Snowflake.

• Advanced SQL programming and query optimization.

• Mandatory experience with Apache Airflow.

• Mandatory experience with dbt (Data Build Tool).

• Strong understanding of ETL/ELT concepts and modern data engineering practices.

• Experience building and maintaining enterprise-scale data pipelines.

• Proficiency in Python for data engineering and automation.

• Experience working with Git and version control.

• Good understanding of data modeling techniques (Star Schema, Snowflake Schema, Dimensional

Modeling).

• Experience working with structured and semi-structured data formats such as JSON, Parquet, and

Avro.

• Strong analytical, debugging, and problem-solving skills.