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# ETL/Data Architect

- **Company:** AbbVie Inc.
- **Location:** Chicago, IL, United States
- **Experience:** Experienced
- **Salary:** $160,555.0 - $178,500.0
- **Contract:** Permanent contract
- **Skills:** Cloud Computing, Code Review, Data Architecture, Information Engineering, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Systems, Data Visualization, Data Warehousing, Power BI, Freeform SQL, Snowflake, Information Technology
- **Published:** May 17, 2026
- **Apply:** https://www.careerjet.com/jobad/us779f463c3768e0ff15f4f82964bcce57

## About the Role

Must have a Bachelor's or foreign education equivalent in Engineering, Computer Science or Biotechnology, or foreign education equivalent & 4 years of experience as a data architect or in related field.
Of experience required, must have 4 years:
(i) working in data integration, data warehousing, cloud-related initiatives, & development &
implementation of data solutions;
(ii) writing complex SQL queries;
(iii) partnering with external vendors or implementation partners to optimize service delivery;
(iv) working with data warehousing, data technologies, & ETL solutions; &
(v) leading end-to-end data engineering & data modelling activities, including design,
implementation, testing, deployment, & support; &
Of experience required, must have 3 years:
(i) applying architecture patterns & data integration design principles;
(ii) working in a matrix organization, balancing customer needs against organizational goals;
(iii) identifying & recommending appropriate product/service offerings to meet functional needs;
(iv) executing project delivery & client relationship management within a technology environment; &
(v) preparing data visualizations using Clik & PowerBI.
Work experience may be gained concurrently.

## Description

* Define & enforce development standards for ETL/Data Warehousing.
 * Design, code, test, & document reusable objects using Snowflake & IICS.
 * Lead full lifecycle Data Warehousing & integration projects from requirements to deployment.
 * Collaborate with Data Engineering team to implement solutions aligned with business needs.
 * Optimize infrastructure & reduce Data platform costs.
 * Implement operational improvements, including processes, controls, & code reviews.


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