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# Data Engineer

- **Company:** Visionaire Partners
- **Location:** St. Louis, MO, United States
- **Experience:** Experienced
- **Salary:** $114,400.0 - $120,640.0
- **Contract:** Temporary contract
- **Skills:** Query Performance, Agile Methodology, Airflow, Databases, Continuous Integration, Directed Acyclic Graph (Directed Graphs), Information Engineering, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Warehousing, Distributed Data Store, Document-Oriented Databases, Python (Programming Language), SQL Databases, Cloud Platform System, Delivery Pipeline, Data Lakes, Kubernetes, Data Delivery, Data Pipelines, Docker
- **Published:** August 30, 2026
- **Apply:** https://www.careerjet.com/job/us492069796a64cb0afe59dd31601fa79e/eaa

## About the Role

* 4+ years of dedicated data engineering experience with a focus on scaling data delivery, automation, and optimizing system resources
 * Advanced expertise in authoring, scheduling, and optimizing complex ETL/ELT pipelines and DAGs using Python, SQL, and Apache Airflow.
 * Demonstrated experience in schema design, query performance tuning, and integrating modern cloud data lakes and data warehousing solutions.
 * Hands-on experience with cloud platform infrastructure, Docker, Kubernetes, and automated CI/CD deployment pipelines.
 * Proven ability to perform root cause analysis, resolve pipeline failures/outages, and maintain comprehensive technical documentation in an Agile environment.

Must be authorized to work in the US. Sponsorships are not available.
Pay range: $55-58/hour W2

## Description

* Author, schedule, and maintain modular ETL/ELT workflows and DAGs using Apache Airflow and custom providers, ensuring seamless data integration across distributed storage and modern cloud data lakes/warehouses.
 * Develop and tune complex SQL scripts and database schemas, continually resolving performance bottlenecks, optimizing cloud resource utilization, and maintaining efficient data warehousing structures.
 * Configure, deploy, and manage data infrastructure using Docker or Kubernetes, integrating custom connectors and CI/CD deployment pipelines under strict operational and security guidelines.
 * Monitor pipeline health to perform root cause analysis during DAG failures or database outages, proactively reducing recurring errors and establishing high data quality standards.
 * Collaborate in an Agile environment to document data architectures and troubleshooting workflows while continuously identifying opportunities to automate and scale data delivery systems.


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