Data Engineer, tastytrade

• You have 2-5 years of professional data engineering experience
• You have expert SQL skills: you think in queries and optimize ruthlessly
• You have real dbt experience, meaning actual production work and not just exposure
• You write solid Python, with production code rather than scripts
• You have hands-on experience with Airflow (or Prefect/Dagster)
• You have experience with a cloud data warehouse (Snowflake, BigQuery, or Redshift)
• You understand the data product lifecycle, standards, and practices
• You know your way around data quality functions like cleansing, standardization, parsing, and validation
• You can design systems and lead projects
• You communicate clearly with non-engineers and engineers alike
• You’re proficient with version control (Git/GitHub) and command line interfaces

Desirable

• We’re looking for a Data Engineer to join our Analytics team. You’ll own data pipeline architecture, upskill those around you, and have real influence on how we build our data platform
• 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. This is a full-scope role: you’ll design systems, make tech decisions, ship, and iterate. If you have a good idea and can execute it, we’d love to learn from you
• Our team works with Snowflake, dbt, Airflow, Tableau, Python, AWS (S3, ECR, EKS), GitHub, ArgoCD, Elementary, and Grafana
• 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
• Write ELT code using modern data engineering practices, including Git and automated testing and deployments
• Debug production data issues when they break (and they will)
• Process, clean, and validate data from a variety of external sources and internal data pipelines
• Lead ad-hoc analysis using internal and external data sources to help teams understand how customers interact with our products
• Collaborate with upstream data producers (Software Engineering/DevOps) and downstream data consumers (Marketing, Product, and Leadership)
• Contribute to data visualization and reporting efforts in Tableau
• Upskill those around you through code review, design collaboration, and knowledge sharing
• Optimize performance, improve processes, and level up team practices