Design and build scalable and efficient data pipelines to transform and load data into Snowflake from various data sources.
Collaborate with data scientists, analysts, and other engineers to understand business requirements and deliver solutions that meet those needs.
Optimize existing data models, queries, and transformations to improve performance, reliability, and scalability.
Develop and maintain DBT projects to manage data transformations, ensuring consistency, versioning, and efficient execution.
Write clean, maintainable, and well-documented SQL code for data transformation and modeling.
Implement data quality checks and monitoring processes to ensure the accuracy and completeness of data.
Work with cloud-based data storage and processing technologies (Snowflake, S3, etc.) to manage large datasets effectively.
Conduct code reviews and ensure adherence to data engineering best practices.
Stay updated with the latest trends in data engineering, cloud technologies, and DBT/Snowflake best practices.
Required Skills and Qualifications:
Proven experience as a Data Engineer, with a strong focus on Snowflake and DBT.
Strong proficiency in SQL and experience working with large, complex datasets.
Hands-on experience with DBT to build, test, and deploy data transformation workflows.
In-depth knowledge of Snowflake data warehouse architecture, features, and best practices.
Experience with cloud platforms (e.g., AWS) and data storage technologies like S3.
Strong understanding of data modeling, ETL/ELT processes, and data transformation techniques.
Ability to optimize queries and transformations for performance and scalability.
Experience working with version control tools (e.g., Git).
Ability to write clear and maintainable code, following industry best practices.
Familiarity with data visualization tools and technologies (e.g., power BI) is a plus.
Strong analytical and problem-solving skills.
Excellent communication and collaboration skills to work effectively with both technical and non-technical teams.
Preferred Skills:
Experience with Python or other programming languages for data engineering.
Familiarity with workflow orchestration tools (e.g., Airflow).
Knowledge of data governance, security, and privacy practices.
Experience with Data Lake architectures and integration.
Exposure to DevOps practices and CI/CD pipelines for data engineering.
Added advantage on Fivetran.
Key job details
About Virtusa
Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 27,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.
Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.
Virtusa is an Equal Opportunity Employer. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government-issued ID during each interview. All candidates must be authorized to work in the USA.
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