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# Data Engineer

- **Company:** COVISTA OF VIRGINIA, INC.
- **Location:** Chicago, IL, United States
- **Experience:** Experienced
- **Salary:** $74,065.0
- **Contract:** Permanent contract
- **Skills:** Airflow, BigQuery, Computer Engineering, Information Engineering, Data Structures, Python (Programming Language), Cloud Services, Software Engineering, SQL Databases, Workflow Management Systems, Information Technology, Data Lineage, Data Pipelines
- **Published:** August 2, 2026
- **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=2903911384-2

## About the Role

* Bachelor's Degree Computer Science, Computer Engineering, Software Engineering, or other related technical field Required.
 * Master's Degree Computer Science, Computer Engineering, Software Engineering, or other related technical field Preferred.
 * Three (3) plus years of experience in building data lakes and cloud data platforms.
 * Experience working with GCP technologies like BigQuery, Composer, GCS, DataStream, Dataflows.
 * Expert knowledge on SQL and Python programming.
 * Experience working with Airflow as workflow management tools and build operators to connect, extract and ingest data as needed.
 * Experience in tuning queries for performance and scalability
 * Experience working in agile environment.
 * Excellent problem-solving and critical thinking skills.

***Applicants must be currently authorized to work in the United States on a full-time basis. Covista will not sponsor applicants for work visas.***

## Description

* Work closely with various business, IT, Analyst and Data Science groups to collect business requirements.
 * Develop, deploy and support high performance data pipelines both inbound and outbound.
 * Optimize data pipelines for performance, scalability, and reliability.
 * Ensure quality of critical data element, prepare data quality remediation plans and collaborate with business and system owners to fix the quality issues at its root.
 * Document the design and support strategy of the data pipelines.
 * Capture, store and socialize data lineage and operational metadata.
 * Troubleshoot and resolve data engineering issues as they arise.


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