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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