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Azure Data Engineer

Job ID : 38697

Job Title : Azure Data Engineer

Location : San Diego, CA

Comapny Name : MSIT

Job Type : Full-Time, Part-Time, Contract, Training

Industry : Information Technology

Salary :  $102700 - $107700  per year

Work Authorization : ["OPT","CPT","Entry Level","F1","H4","L1","H1 Visa","TN Permit Holder","Green Card Holder","Canadian Citizen","All EAD","US Citizen"]

No. of Positions : I have ongoing need to fill this role

Posted on : 02-03-2025

Required Skills : Data warehouse, Machine learning, Problem solving.

Benefits : Medical Insurance, Dental Insurance, Vision Insurance, 401K, Life Insurance

Job Description :

Responsibilities:

  • Perform ETL, ELT operations and administration using modern tools, programming languages and systems securely and in accordance with enterprise data standards.
  • Assemble, model, transform large complex sets of data that meet non-functional and functional business requirements into a format that can be analyzed.
  • Automate data processing of data from multiple data sources.
  • Develop, deploy and version control code for data consumption, reuse for APIs.
  • Employ machine learning techniques to create and sustain data structures.
  • Perform root cause analysis on external and internal processes and data to identify opportunity for improvement, resolve data quality issues
  • Lead data-related workshops with stakeholders to capture data requirements and acceptance criteria.

Qualifications:

  • Minimum bachelor’s degree in: Data Science, Business Intelligence, Statistics, Computer Engineering or related field, or the equivalent combination of education, professional training, and work experience.
  • 5 or more years performing duties related to data engineering.
  • Expert proficiency in at least one of these programming languages: Python, NoSQL, SQL, R, and competent in source code management.
  • Build processes supporting data transformation, data structures, metadata, dependency, and workload management.

Key Skills:

  • ETL.
  • Data modeling.
  • Data pipelining.
  • Data security and compliance.
  • Data warehouse.
  • Machine learning.
  • Problem solving.
  • Big data technologies.
  • Cloud computing.

Company Details :

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