Data Engineer

tastytrade; United States; Sur place; USD 120 000 - 180 000; Plein temps

Avantages offerts par ce poste

Medical plans

Dental & Vision

401(k) with company match

Paid time off

Parental leave

Commuter benefits

Gym membership

Stock purchase options

Résumé du poste

tastytrade is seeking a Data Engineer to join our Analytics team in Chicago. You’ll own data pipeline architecture, upskill teammates, and influence how we build our data platform.

You’ll work with a full stack data team on end-to-end data pipelines, feature generation, and executive dashboards. Expect design decisions, production code, and collaboration across engineering, analytics, and leadership.

Qualifications

• 2–5 years of professional data engineering experience.
• Hands-on with Airflow, dbt, Python, and SQL in production.
• Experience with cloud data warehouses (Snowflake, BigQuery or Redshift).

Responsabilités

• Design and build scalable data pipelines to support dashboards and analytics.
• Own pipeline architecture, performance, and observability.
• Make architectural decisions, including schema design and tooling.
• Write ELT code with Git-based deployments and tests.
• Collaborate with data scientists, analysts and engineers on data products.
• Lead data quality initiatives and data validation processes.

Connaissances

Python

SQL

Airflow

dbt

Git/GitHub

Kubernetes

CI/CD

Data quality

Agile

Communication

Outils

Snowflake

BigQuery

Redshift

Prefect

Dagster

Tableau

ArgoCD

Excel

Description du poste

• 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

Benefits

• 3 Medical Plans Choice
• Dental & Vision Benefits
• Generous Paid Time Off
• Paid Holidays - All Market Holidays Off
• 401(k) with Company Match
• Generous Parental Leave
• Disability Leave & Disability Insurance
• Commuter Benefits
• Pet Insurance
• Charitable Donation Matching
• Subsidized Engineering Training Program
• Gym Membership Reimbursement
• Performance Bonuses
• Wellness & Mental Health Programs
• Stock Purchase Options
• Healthcare FSA
• Two Paid Volunteer Days Off
• Fully-stocked Kitchen with Snacks and Drinks
• Onsite Gym
• Casual Dress
• Sustainable Work Day
• CTA stop a block away, Shuttle to/from Metra
• Shared rooftop with greenery overlooking the city
• West Loop Location - Chicago’s Tech Center
• Daily Catered Lunch

You have hands-on experience with Airflow (or Prefect/Dagster)You write solid Python, with production code rather than scriptsYou have real dbt experience, meaning actual production work and not just exposureYou have 2-5 years of professional data engineering experienceYou know your way around data quality functions like cleansing, standardization, parsing, and validationYou’re proficient with version control (Git/GitHub) and command line interfacesYou have expert SQL skills: you think in queries and optimize ruthlesslyYou understand the data product lifecycle, standards, and practicesYou have experience with a cloud data warehouse (Snowflake, BigQuery, or Redshift)You can design systems and lead projectsYou communicate clearly with non-engineers and engineers alikeExperience with agile development practices and the project lifecycleAdvanced Airflow patterns and custom operatorsFinancial services backgroundData quality frameworks (Elementary, Great Expectations, Monte Carlo)CI/CD and DevOps practicesKubernetes or infrastructure-as-code experience