Virtusa

Snowflake DBT

Job Description

Snowflake Development & Optimization:
Write complex SQL queries against Snowflake, including optimization and troubleshooting of queries for improved performance.
Develop ETL/ELT scripts in Python, Unix, and other scripting languages to extract, load, and transform data between systems.
Utilize Snowflake utilities such as SnowSQL, SnowPipe, Streams, Tasks, and Stored Procedures to automate data pipeline management and enhance data workflows.
Leverage Time Travel for data recovery and audit purposes, ensuring data integrity across historical states.
ETL Pipeline Development:
Design, implement, and maintain ETL pipelines using DBT (Data Build Tool) for data transformation and automation tasks.
Work with various ETL tools, primarily DBT, and integrate them with Snowflake and other systems as required.
Optimize and ensure the scalability of data pipelines to handle large volumes of data.
Data Modeling & Architecture:
Develop data models, including conceptual, logical, and physical models, entity-relationship diagrams (ERDs), star schemas, and third normal form (3NF) to support analytical requirements.
Perform source-to-target mapping to ensure data accuracy and completeness in data transformation and integration.
Cloud Integration & Automation:
Work with AWS services like IAM, S3, ECS, CloudFormation, and CloudWatch to integrate Snowflake with other cloud applications and ensure continuous monitoring, security, and automated deployment.
Automate infrastructure deployments using CloudFormation and ensure system scalability and resiliency.
Collaboration & Problem Solving:
Work effectively within a global team environment, collaborating with other data engineers, analysts, and stakeholders.
Provide solutions to complex problems using creative and analytical approaches to continuously improve processes.
Ensure that data solutions adhere to performance, security, and compliance standards.
Documentation & Communication:
Write clear and concise technical documentation for developed pipelines, queries, data models, and processes.
Communicate complex technical information to both technical and non-technical stakeholders.
Maintain detailed records of data integration tasks, ETL processes, and data quality metrics.
Snowflake
Expertise in Snowflake SQL, including advanced query writing and optimization.
Hands-on experience with Snowflake tools and utilities such as SnowSQL, SnowPipe, Streams, Tasks, Time Travel, and Metadata Manager.
Experience with Snowflake Data Sharing and Stored Procedures.
ETL & Data Transformation:
Strong experience with ETL/ELT processes, including the development and optimization of DBT scripts for data transformation.
Proficiency in advanced SQL and Python scripting for automating data tasks and pipeline management.
Cloud & AWS:
Experience with AWS services, including IAM, S3, ECS, CloudFormation, and CloudWatch for cloud-based data integration and automation.
Familiarity with setting up and monitoring cloud-based data infrastructures and applications.
Data Modeling:
Proficiency in data modeling techniques, including the creation of conceptual, logical, and physical data models.
Experience with entity-relationship diagrams (ERDs), star schemas, and third normal form (3NF).
Agile Methodologies:
Familiar with Agile delivery processes and practices for iterative and collaborative development.
Experience working in Agile environments, including participating in sprint planning, backlog grooming, and daily standups.


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