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# Data Engineer

- **Company:** Tastylive, Inc.
- **Location:** Chicago, IL, United States
- **Experience:** Experienced
- **Salary:** $130,000.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** Sql Data Warehouse, Airflow, Amazon Web Services, Amazon S3, Data Analysis, Automation of Tests, BigQuery, Command-Line Interface, Code Review, Continuous Integration, Information Engineering, Data Governance, Data Infrastructure, Software Debugging, DevOps, Github, Python (Programming Language), Operational Databases, Parsing, Standard Sql, Software Engineering, Tableau (Software), Feature Engineering, Great Expectations (Foster Youth College-readiness and Support Program), Snowflake, Grafana, Git, Build Management, Kubernetes, Production Code, Software Version Control, Data Pipelines
- **Published:** October 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=31d6da66a04d0d70

## About the Role

* 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

Preferred Qualifications

 * Kubernetes or infrastructure-as-code experience

 * CI/CD and DevOps practices

 * Data quality frameworks (Elementary, Great Expectations, Monte Carlo)

 * Financial services background

Advanced Airflow patterns and custom operators
*

 * Experience with agile development practices and the project lifecycle

## Description

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.

What You'll Do

 * 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