Job Description:
• Design, develop, and maintain scalable data transformation pipelines using SQL, dbt, and Jinja templating.
• Build and maintain robust dimensional data models to support analytics, reporting, and business intelligence.
• Develop reusable dbt models, macros, packages, tests, and documentation.
• Translate business requirements into scalable analytical data models.
• Design and optimize analytical data marts and warehouse structures.
• Implement best practices for dimensional modeling, fact tables, and dimension tables.
• Optimize SQL workloads using clustering, partitioning, materialization strategies, and performance tuning techniques.
• Ensure high-performance data pipelines and efficient query execution on large datasets.
• Implement automated testing and validation frameworks within dbt.
• Ensure consistency and accuracy of business metrics across reporting platforms.
• Support data governance initiatives, privacy controls, and access management requirements.
• Maintain high standards of data quality, reliability, and documentation.
• Partner with Product, Analytics, BI, and Data teams to understand business requirements.
• Participate in Agile ceremonies and sprint planning activities.
• Perform code reviews and maintain development best practices.
• Collaborate with distributed global teams for successful project delivery.
Requirements:
• 8+ years of experience in Data Engineering / Analytics Engineering
• 3+ years of hands-on experience with dbt
• Strong expertise in Advanced SQL
• Strong experience in Snowflake
• Experience with Amazon Redshift
• Expertise in Dimensional Data Modeling (Star Schema, Snowflake Schema)
• Experience with Data Warehousing Concepts
• Knowledge of Jinja Templating
• Working knowledge of Python
• Experience with Git, CI/CD, and Agile methodologies
• Experience implementing Data Quality, Testing, and Governance Frameworks
Benefits:
• Health insurance
• Flexible work arrangements
• Professional development opportunities