You would be working in a fast paced environment as part of the team of data engineers, designing and implementing solutions that provide business-critical insights. You will be responsible for design of data warehouse schemas as well as end-to-end design and implementation of fault tolerant and scalable data processing pipelines using a variety of technologies for orchestrating data movement. The primary technologies you would be using are Snowflake, DBT and Airflow.

Job Responsibilities

• Design and implement data warehouse schemas to store large data sets that can be easily and efficiently queried and joined together for reporting and analytical purposes.
• Design and develop ETL/ELT pipelines to efficiently move and aggregate data, while optimizing for maximum code and data reuse.
• Collaborate with other team members on improvements to existing systems
• Investigate data anomalies and provide quick resolutions.
• Provide technical support to business users and analysts.

Requirements

• 3+ years of working experience with large scale data warehouse systems
• Very strong knowledge of SQL and data manipulation best practices
• Experience in building efficient and fault tolerant ELT/ETL data pipelines
• Very strong knowledge of working with large scale datasets
• Ability to investigate data discrepancies and find the root cause
• Ability to write test cases for data validation
• Ability to write clear documentation
• Very strong knowledge of data modeling and data warehouse design
• Knowledge of Snowflake is preferrable
• Knowledge of DBT, Jinja scripting and Airflow is a big plus
• Ability to translate business requirements into functional specifications
• Ability to quickly adapt to changes in requirements and to effectively work on geographically diverse cross-functional teams
• Excellent written and verbal communication skills