Design and optimize scalable data models, queries, and storage solutions to improve performance and efficiency across the platform
Maintain and enhance a custom-built query engine, ensuring flexibility and optimal performance as customer needs evolve
Build for scale. Onboarding customers with larger datasets and increasingly complex analytical requirements is a core part of the job
Collaborate with engineers and business stakeholders to develop data-driven features that solve real customer problems
Continuously improve engineering processes and data infrastructure to enable rapid development and iteration

Requirements

Proficiency in SQL and hands-on experience with cloud-based databases and data storage solutions (e.g., Snowflake, Databricks, BigQuery)
Proficiency in Python
Hands-on experience building and optimizing ETL pipelines and frameworks
Deep understanding of data modeling principles and data warehouse design for analytics
Strong problem-solving and debugging skills in large-scale data environments
Ability to communicate complex data concepts clearly to business stakeholders and cross-functional teams
Bonus If You Have...
Experience with Snowflake data stores, AWS Step Functions, and AWS Lambda
Exposure to machine learning pipelines and model deployment in data environments

Benefits

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Applicant Tracking System Keywords

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Hard Skills & Tools

SQLPythonETL pipelinesdata modelingdata warehouse designdebuggingmachine learning pipelinesmodel deployment

Soft Skills

problem-solvingcommunicationcollaboration