Senior Data Engineer

Akaasa Technologies

Minneapolis, MN, United States

about 2 months ago

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Role details

Contract type

Temporary to permanent

Employment type

Full-time (> 32 hours)

Experience level

Expert

Compensation

$60,000.0 - $85,000.0

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Artificial Intelligence Microsoft Azure Big Data Cloud Database Data Infrastructure Data Transformation Distributed Computing Environment MongoDB NoSQL Data Streaming Data Processing Azure Data Factory

+6 more

Data Lakes Data Analytics Apache Kafka Data Management Data Pipelines Databricks

Job description

Our client is seeking a Senior Data Engineer to design, develop, and modernize enterprise-scale data platforms. The ideal candidate will have strong expertise in Azure, Databricks, Azure Data Factory (ADF), Kafka, and large-scale data architecture, along with experience delivering cloud-based data migration and modernization initiatives., * Design and implement scalable cloud-based data solutions using Azure, Databricks, and Azure Data Factory (ADF).

Build and support enterprise data architectures capable of handling high-volume data processing.
Develop and optimize data pipelines for ingestion, transformation, and integration.
Lead large-scale data migration initiatives while ensuring data quality and consistency.
Work with modern data platforms including Data Lakes, Kafka, and NoSQL databases.
Collaborate with cross-functional teams to deliver secure, reliable, and scalable data solutions.
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Requirements

Note: This position was previously shared with a different location. Candidates must be local to Chicago, IL or Minneapolis, MN and able to work onsite 3 4 days per week., * Strong experience designing and implementing cloud-based data solutions using the Azure ecosystem.

Hands-on expertise with Azure Databricks and Azure Data Factory (ADF).
Experience designing large-scale enterprise data architectures and high-volume data platforms.
Strong knowledge of Kafka for event streaming and distributed data processing.
Proven experience leading large-scale data migration projects.
Hands-on experience with Data Lakes and NoSQL databases, including MongoDB.
Strong understanding of Azure data services for storage, integration, and analytics.
Exposure to AI-enabled data platforms and modernization initiatives.