Engineer

TATA Consulting Services•Raleigh, NC

41d•$100,000 - $110,000

About The Position

A Job Description for a DBT Developer with 3-5 years of experience, focusing on macros, modeling, and hands-on SQL within a Snowflake platform, would typically include the following: Job Title: DBT Developer (Snowflake) Experience: 3-5 years Roles and Responsibilities: DBT Development & Data Transformation: Design, develop, and maintain robust and scalable data transformation pipelines using dbt on the Snowflake platform. DBT Macro Development to Create and utilize Jinja-based DBT macros to promote code reusability, modularity, and dynamic SQL generation within DBT projects. Data Transformation & Orchestration to Implement and manage data transformation pipelines using DBT, integrating with various data sources and ensuring efficient data flow. Utilize advanced dbt concepts, including macros, materializations (e.g., incremental, view, table), snapshots, and configurations to build efficient data models. Write highly optimized and complex SQL queries for data manipulation, cleaning, aggregation, and transformation within dbt models. Implement and enforce best practices for dbt project structure, version control (Git), documentation, and testing. Data Modeling: Collaborate with data analysts, engineers, and business stakeholders to understand data requirements and translate them into effective data models (e.g., star schema, snowflake schema). Design and implement logical and physical data models within dbt to support analytical and reporting needs. Snowflake Platform Expertise: Leverage Snowflake features and functionalities for performance optimization, including virtual warehouses, clustering, caching, and query optimization. Manage and optimize data ingestion and integration processes from various sources into Snowflake. Collaboration & Communication: Work closely with cross-functional teams to understand business requirements, troubleshoot issues, and deliver high-quality data solutions. Participate in code reviews, provide constructive feedback, and ensure adherence to coding standards. Communicate technical concepts effectively to both technical and non-technical audiences. Quality & Governance: Ensure data quality, integrity, and lineage throughout the data transformation process. Implement and maintain DBT tests to ensure data quality, integrity, and adherence to business rules. Implement and maintain data governance policies and procedures within the dbt environment. Develop and execute automated tests for dbt models to ensure data accuracy and reliability. Continuous Improvement: Stay updated with the latest dbt and Snowflake features and best practices. Identify opportunities for process improvements and implement automation where appropriate.

Requirements

Proven hands-on experience with dbt in a production environment, including extensive use of macros and advanced modeling techniques.
Expert-level proficiency in SQL for data querying, manipulation, and transformation.
Strong experience with Snowflake, including performance tuning and optimization.
Solid understanding of data warehousing concepts and ETL/ELT processes.
Experience with version control systems, particularly Git.
Familiarity with data modeling principles (star schema, snowflake schema).
Excellent problem-solving and analytical skills.
Strong communication and collaboration abilities.

Responsibilities

Design, develop, and maintain robust and scalable data transformation pipelines using dbt on the Snowflake platform.
DBT Macro Development to Create and utilize Jinja-based DBT macros to promote code reusability, modularity, and dynamic SQL generation within DBT projects.
Implement and manage data transformation pipelines using DBT, integrating with various data sources and ensuring efficient data flow.
Utilize advanced dbt concepts, including macros, materializations (e.g., incremental, view, table), snapshots, and configurations to build efficient data models.
Write highly optimized and complex SQL queries for data manipulation, cleaning, aggregation, and transformation within dbt models.
Implement and enforce best practices for dbt project structure, version control (Git), documentation, and testing.
Collaborate with data analysts, engineers, and business stakeholders to understand data requirements and translate them into effective data models (e.g., star schema, snowflake schema).
Design and implement logical and physical data models within dbt to support analytical and reporting needs.
Leverage Snowflake features and functionalities for performance optimization, including virtual warehouses, clustering, caching, and query optimization.
Manage and optimize data ingestion and integration processes from various sources into Snowflake.
Work closely with cross-functional teams to understand business requirements, troubleshoot issues, and deliver high-quality data solutions.
Participate in code reviews, provide constructive feedback, and ensure adherence to coding standards.
Communicate technical concepts effectively to both technical and non-technical audiences.
Ensure data quality, integrity, and lineage throughout the data transformation process.
Implement and maintain DBT tests to ensure data quality, integrity, and adherence to business rules.
Implement and maintain data governance policies and procedures within the dbt environment.
Develop and execute automated tests for dbt models to ensure data accuracy and reliability.
Stay updated with the latest dbt and Snowflake features and best practices.
Identify opportunities for process improvements and implement automation where appropriate.