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Azure Data Engineer

Cargill, Incorporated
Atlanta, GA, United States
24 days ago
Apply on www.careerjet.com
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Working hours
Regular working hours
Job source
www.careerjet.com

Tech stack

Microsoft Azure Cloud Database Information Engineering Data Integration Extract Transform Load (ETL) Data Warehousing Python (Programming Language) Power BI Azure Data Lake SQL Databases Enterprise Data Management Azure Data Factory
+8 more
Git Microsoft Fabric Data Lakes Pyspark Terraform Azure Synapse Analytics Data Pipelines Databricks

Job description

We are seeking an experienced Azure Data Engineer to design, develop, and maintain scalable data pipelines and cloud-based data solutions. The ideal candidate will have strong experience with Azure data services, ETL development, data warehousing, and data integration.

Requirements

  • 6+ years of Data Engineering experience
  • Azure Data Factory
  • Azure Data Lake Storage
  • Azure Synapse Analytics
  • SQL and Python
  • ETL/ELT development
  • Data modeling and data warehousing
  • Data integration and pipeline development
  • Azure DevOps and Git

Preferred Skills:

  • Databricks
  • PySpark
  • Delta Lake
  • Microsoft Fabric
  • Power BI
  • Terraform
  • Azure certification
  • Experience with large enterprise data environments

Hiring #W2 #AzureDataEngineer #Azure #DataEngineering #AzureDataFactory #Synapse #Databricks #Python #PySpark #SQL #CloudJobs #ITJobs #TechJobs

About the company

Cargill is committed to providing food and agricultural solutions to nourish the world in a safe, responsible, and sustainable way. Sitting at the heart of the supply chain, we par…

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.careerjet.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

Moments

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3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

4:32 min

Harnessing Spark with Python using PySpark and Py4J

Ayon Roy · LIVE

1:24 min

Moving the semantic layer upstream to avoid vendor lock-in

Piotr Menclewicz Piotr Menclewicz · Europe 2026 Virtual

1:46 min

Traditional data architecture before Microsoft Fabric

Dr. Alexander Wachtel Dr. Alexander Wachtel +1 · World Congress 2025

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

Videos

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LIVE • almost 6 years ago

PySpark - Combining Machine Learning & Big Data

Ayon Roy

How a Small Team Shrank a Microsoft Monorepo by 94% thumbnail
33:23
Coffee With Developers • almost 2 years ago

How a Small Team Shrank a Microsoft Monorepo by 94%

Jonathan Creamer

Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG thumbnail
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Europe 2026 Virtual • 2 months ago

Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG

Piotr Menclewicz

From Messy Queries to Scalable Systems - How Data Engineering actually works thumbnail
31:15
World Congress 2026 Europe • about 2 months ago

From Messy Queries to Scalable Systems - How Data Engineering actually works

Sandhya Menon

Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents thumbnail
26:58
World Congress 2025 • about 1 year ago

Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents

Dr. Alexander Wachtel, Hanna Schwab

Empowering Retail Through Applied Machine Learning thumbnail
22:41
World Congress 2024 • about 2 years ago

Empowering Retail Through Applied Machine Learning

Christoph Fassbach, Daniel Rohr

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