tastylive
Data Engineer
Chicago, Illinois · Mid
Sponsorship not specifiedDetected 3 days ago
PythonFull-Stack DevelopmentCode ReviewGitSQLSnowflakeAWSDevOpsAirflowdbtData EngineeringData VisualizationDesign SystemsTest AutomationLeadershipCollaborationArgo CD
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Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
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About the role
- We're looking for a Data Engineer to join our Analytics team.
- You'll be part of a full stack data team of data scientists, data engineers, and analysts who take full ownership of our data pipelines and feature generation.
Responsibilities
- Design and build scalable data pipelines using dbt, Python, Airflow, and Snowflake to support business processes, such as our executive reporting dashboards
- Own pipeline architecture and performance, and drive strategic initiatives to improve our data platform
- Make architectural decisions, including schema design, tool selection, and trade-offs
- Own data quality and observability, and build the infrastructure that keeps our data right
- Process, clean, and validate data from a variety of external sources and internal data pipelines
- Collaborate with upstream data producers (Software Engineering/DevOps) and downstream data consumers (Marketing, Product, and Leadership)
- Upskill those around you through code review, design collaboration, and knowledge sharing
- Optimize performance, improve processes, and level up team practices
Requirements
- You have 2-5 years of professional data engineering experience
- If you have a good idea and can execute it, we'd love to learn from you.
Skills
- You have real dbt experience, meaning actual production work and not just exposure
- You write solid Python, with production code rather than scripts
- you think in queries and optimize ruthlessly
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Company info
- Data Engineer
- Chicago, IL (Hybrid, 3 days/week)
- Lead ad-hoc analysis using internal and external data sources to help teams understand how customers interact with our products
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This listing is sourced directly from tastylive's careers page and normalized into a canonical job model.