Data Engineer at Seattle, WA(Local)

Seattle, WA Seattle WA 98199

Date : Sep-10-21

Data Engineer at Seattle, WA(Local)

Seattle, WA

Sep-10-21

Work Authorization

US Citizen
GC
H1B
OPT EAD, CPT EAD, GC EAD, L2 EAD, H4 EAD, TN EAD

Preferred Employment

Corp-Corp
W2-Permanent
W2-Contract
1099-Contract
Contract to Hire

Job Details

Experience

:

Architect, Senior, Midlevel, Junior

Rate/Salary ($)

:

market rate

Duration

:

6 months

Sp. Area

:

Data Warehousing/ETL

Sp. Skills

:

Data Engineer

Consulting / Contract

H1B Sponsorship Available

Required Skills :

Data Engineer, Data Modeling, Big Data, Data Warehousing, ETL

Preferred Skills :

Domain :

Work Authorization

US Citizen
GC
OPT EAD, CPT EAD, GC EAD, L2 EAD, H4 EAD, TN EAD
H1B

Preferred Employment

Corp-Corp
W2-Permanent
W2-Contract
1099-Contract
Contract to Hire

Job Details

Experience

:

Architect, Senior, Midlevel, Junior

Rate/Salary ($)

:

market rate

Duration

:

6 months

Sp. Area

:

Data Warehousing/ETL

Sp. Skills

:

Data Engineer

Consulting / Contract

H1B Sponsorship Available

Required Skills :

Data Engineer, Data Modeling, Big Data, Data Warehousing, ETL

Preferred Skills :

Domain :

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Nityo Infotech
Plainsboro, NJ
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Job Description :

Role – Data Engineer

Locations – Seattle, WA (Local)

Duration: Long Term

Skills:

Job Qualifications:

Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline.
5+ years of experience as a Data Engineer or in a similar role.
Demonstrated experience in ETL/ELT, data modeling, data warehouse technical architecture, infrastructure components and reporting/analytic tools.
5+ years of hands-on experience in writing complex, highly-optimized SQL queries across large data sets.
3+ years of experience in scripting languages like Python etc.
Experience working with AWS big data technologies (Redshift, S3, EMR, Glue).
Experience coding and automating processes.
Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy.

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