Job Details

ID #49572082
State Texas
City Houston
Job type Permanent
Salary USD USD130,000 - USD140,000 USD130000 - USD140000
Source Irvine Technology Corporation (ITC)
Showed 2023-03-28
Date 2023-03-28
Deadline 2023-05-27
Category Et cetera
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Onsite BI Data Engineer (ETL + Azure)

Texas, Houston, 77056 Houston USA

Vacancy expired!

Searching for a full-time employee to execute strategic projects to create competitive edge solutions combining design, data, and software engineering while providing superb customer service. The ideal candidate will have experience cleaning data, reporting and dashboarding,

ETL, excellent SQL skills, performance tuning, database architecture and design and all the other lessons learned in a long career working with data. Fantastic

Azure Synapse and Azure Spark & SQL skills are preferred for this role.

Responsibilities:
  • Collaborate with data scientists, product management, and web engineers to deliver value and project outcomes.
  • Convert prototype models and data pipelines built by data scientists for use in production.
  • Work closely with the Architect and offer suggestions on Data warehouse & pipeline designs.
  • Work with Application Team/IT to improve workflows in the source apps to improve quality of feeds into the warehouse.
  • Able to create internal reports/dashboard in

    SSRS/Power BI for custom monitoring of ETL pipelines/Warehouse health.
  • Balance long-term code health and maintainability with business needs.
  • Profiling and performance tuning of production code.

Qualifications:
  • 7+ years with

    ETL (SSIS or similar) using multiple sources
  • Experience working on projects within the cloud ideally

    Azure
  • Strong development background with experience in T-SQL
  • 2+ Years working with

    Azure Synapse (formerly Azure DW) in a Production environment, using both

    Spark pools & SQL pools
  • 2+ Years Building pipelines/

    ETL using Azure Data Factory in a Production environment
  • Had a major role in 1+

    Migrations/Conversions between one data source and another

Vacancy expired!

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