Enterprise Data Engineer

LEDGENT

San Diego, CA, United States

1 day ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Compensation

$105,000.0 - $132,000.0

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Agile Methodology Business Analytics Applications Microsoft Azure Continuous Integration Extract Transform Load (ETL) Data Mining Data Warehousing Dimensional Modeling Python (Programming Language) Microsoft SQL Server Online Analytical Processing Online Transaction Processing

+16 more

Scrum Methodology Power BI Azure Data Lake Software Engineering SQL Server Reporting Services SQL Server Integration Services Azure Data Factory Apache Spark Git Microsoft Fabric Information Technology Data Analytics Star Schema Azure Synapse Analytics Software Version Control Databricks

Requirements

Bachelor’s degree in Computer Science, Information Technology, Software Development, or a related field, or an equivalent combination of education and experience.
5+ years of experience in database engineering and design within OLTP and OLAP environments.
5+ years of experience developing data extraction, transformation, and loading processes using SSIS, Azure Data Factory, Python, or similar technologies.
5+ years of experience developing enterprise reporting and analytics solutions using Power BI and SSRS.
Advanced expertise with SQL Server 2016 and newer versions.
Strong understanding of:
Data warehousing concepts
Dimensional modeling and star schema design
Data modeling and normalization
ETL/ELT development
Data quality and governance
Reporting and business intelligence solutions
Experience working in Agile and Scrum environments.

Preferred Qualifications

Experience with Microsoft Azure data and analytics technologies, including:
Azure Data Factory
Azure Synapse Analytics
Azure Data Lake Storage
Databricks
Apache Spark
Microsoft Fabric
Experience with Azure DevOps, Git, CI/CD practices, and source control management.
Python development experience.
Experience supporting enterprise-scale data and analytics environments.