Sr. Data Engineer (data flows and integration pipelines) in Minneapolis, MN will start remote but then will need to relocate


From:
Bhavya Maheshwari,
Group Nine LLC
bhavya.m@groupninellc.com
Reply to:   bhavya.m@groupninellc.com

Hi,

I have an urgent requirement with one of my clients, details given below. If you find yourself suitable for the position, please send me your latest updated resume along with contact details. Please include your employer details as well.

Job Title

Sr. Data Engineer (data flows and integration pipelines)

 

Project Location

Minneapolis, MN – will start remote but then will need to relocate

 

Duration

08-31-2021 (12+month)

 

Mode of interview

Phone and Skype

 

 

but a true engineering in this space who has actually had to build out data flows, frameworks and integration pipelines with big data tools like Hadoop.

 

**Candidates will need to relocate to MN after Covid restrictions are lifted.

Great Comm. Skills

10-15 Years of solid exp.

 

Required Skills

•             Strong problem solving skills

•             Scripting/development skills – Python, Spark, Java

•             Database experience – SQL queries, basic database design skills, testing skills

•             DevOps experience – GIT/Jenkins

•             Ability to learn and adapt to changing environment.

•             Strong Linux (R and R connect within this), Python, Hadoop, SQL   (Hadoop instance is currently on-premises), ETL tools (Informatica, StreamSets)

•             Productionalize and maintain data frameworks joining information from multiple databases

•             Productionalize and maintain workflows and analytical models

•             Support and maintenance of data science tools, including package installation and proactive management within R server

 

Preferred Skills               

•             Cloud eventually mindset

•             Continuous integration/docker support(or other containerization technologies)

•             Identify and recommend enhancements to improve Data Scientist computational productivity

•             Collaborate with data scientists, data engineering, and other technology teams to implement the above and proactively identify other potential opportunities

 

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