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Bartech Staffing / Corporate Headquarters, MI

4.66
from 6042 reviews
96% highly recommended
 
Rating Breakdown
5 star
6,270 4 star
1,651 3 star
317 2 star
78 1 star
40
G.R.E.A.T Traits

Genuine

4.73

Responsive

4.70

Experienced

4.67

Advisor

4.58

Transparent

4.63
People Who Recommend
96%
Reviews in Last 12 Months
466
Reviews
Rating Past 12 Months Bartech Staffing continuously reviews to keep ratings current.
4.66 from 466 reviews

SERGIU M. DRE/Pack Lead LV Battery 5.00

2 months ago

About Jillian Dunn:

Professional
Highly Recommended

Helpful? Report

Sai K. Senior SAP Analyst 5.00

2 months ago

About Barry Andis:

Great response
Highly Recommended

Helpful? Report

Mohamed F. Software Test AND Validation Engineer 5.00

2 months ago

About Jillian Dunn:

Highly Recommended

Helpful? Report

LEVI G. Project Manager/ Technical Sales 5.00

3 months ago

About Heather McRae:

Highly Recommended

Helpful? Report

Osama K. Data Analytics Intern 5.00

3 months ago

About Barry Andis:

Highly Recommended

Helpful? Report

Scarlet M. Lead Production Supervisor/WMS Specialist 5.00

3 months ago

About Jillian Dunn:

Highly Recommended

Helpful? Report

Emanuel B. Senior NPD Buyer Remote 5.00

3 months ago

About Heather McRae:

Highly Recommended

Helpful? Report

June H. Marketing Campaign Specialist B2C 5.00

3 months ago

About Heather McRae:

Very nice, made the job searching experience a little less intimidating!
Highly Recommended

Helpful? Report

Alfredo C. Market Risk Manager Crude AND Products 5.00

3 months ago

Highly Recommended

Helpful? Report

Nicolas R. Senior Data Engineer Cloud AND Data Platform Leader 5.00

3 months ago

About Barry Andis:

Senior Data Engineer with 9+ years of experience designing scalable data pipelines, optimizing ETL workflows, and building analytics platforms. Skilled in Python, SQL, Spark, and Airflow, with deep expertise in cloud data solutions (AWS, GCP), data lakes, and warehouse technologies like Snowflake and Redshift. Proven track record in enabling data-driven decisions, improving pipeline efficiency, and leading cross-functional data initiatives in fast-paced environments.
Highly Recommended

Helpful? Report

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