Key skills
AWSBigQueryCloudETLPythonSQLMachine LearningAnalyticsSnowflakeDatabricksLambda
About this role
Role Overview
- 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
Tech Stack
- AWS
- BigQuery
- Cloud
- ETL
- Python
- SQL
Benefits
- Offers Equity