Snowflake Data Engineer

with mandatory expertise in Snowflake and dbt (data build tool)

Roles & Responsibilities

Key Responsibilities:

Technical Leadership & Data Engineering:

• Lead end-to-end data warehousing projects using

  Snowflake and dbt (mandatory skills)

• Design and implement scalable data models, ETL/ELT pipelines, and data architecture in Snowflake
• Develop and optimize dbt models, transformations, and data workflows for efficient analytics
• Work with AWS data services - Aurora, RDS, DMS, DynamoDB - for data integration and migration
• Optimize SQL, PL/SQL queries and database performance (Oracle, PostgreSQL, etc.)
• Implement CDC (Change Data Capture) and real-time data processing solutions
• Ensure data governance, quality, and best practices in data engineering

Requirement Analysis & Customer Handling:

• Collaborate with stakeholders to gather, analyze, and document business requirements
• Handle Change Requests (CRs) and provide technical solutions aligned with business needs
• Act as a bridge between business teams and technical teams for data-driven decision-making

Team Leadership & Mentorship:

• Guide and mentor junior data engineers in Snowflake, dbt, and modern data stack best practices
• Ensure adherence to data security, compliance, and scalability principles

Mandatory Skills & Experience:

• 6-13 years of hands-on experience in Data Engineering, Data Warehousing, and Data Modeling
• Expert-level proficiency in Snowflake and dbt (data build tool) - Mandatory
• Strong expertise in:
• AWS Data Services (Aurora, RDS, DMS, DynamoDB)
• Oracle, PL/SQL, SQL, and database optimization
• ETL/ELT pipelines & Data Integration
• Data Architecture & Dimensional Modeling (Star Schema, Kimball, etc.)
• Experience in customer handling, requirement gathering, and solution design

Preferred Qualifications:

• Certification in Snowflake, dbt, or AWS Data Technologies
• Experience with Python, PySpark, or other scripting languages
• Knowledge of CI/CD pipelines for data workflows