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Datasets Jobs in Michigan (NOW HIRING)

Architect and maintain data lakes and warehouses (Snowflake, Redshift) and implement dbt-based data modeling for analytics-ready datasets. * Build and manage orchestration workflows using Apache ...

Strengthen financial reporting accuracy through hands-on support of quarterly product and regional reporting, applying a solid understanding of financial statements and large datasets. * Improve ...

Strengthen financial reporting accuracy through hands-on support of quarterly product and regional reporting, applying a solid understanding of financial statements and large datasets. * Improve ...

Strengthen financial reporting accuracy through hands-on support of quarterly product and regional reporting, applying a solid understanding of financial statements and large datasets. * Improve ...

Advanced Excel proficiency and comfort with large datasets to efficiently extract, consolidate, and analyze BOM and subledger data. * Familiarity with ERP systems (SAP, Oracle, or similar) to support ...

Strengthen financial reporting accuracy through hands-on support of quarterly product and regional reporting, applying a solid understanding of financial statements and large datasets. * Improve ...

Strengthen financial reporting accuracy through hands-on support of quarterly product and regional reporting, applying a solid understanding of financial statements and large datasets. * Improve ...

Strengthen financial reporting accuracy through hands-on support of quarterly product and regional reporting, applying a solid understanding of financial statements and large datasets. * Improve ...

Strengthen financial reporting accuracy through hands-on support of quarterly product and regional reporting, applying a solid understanding of financial statements and large datasets. * Improve ...

Strengthen financial reporting accuracy through hands-on support of quarterly product and regional reporting, applying a solid understanding of financial statements and large datasets. * Improve ...

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Datasets information

What is the difference between Datasets vs Data Analysts?

AspectDatasetsData Analysts
Required credentialsNone specific; often familiarity with data formats and toolsBachelor's degree in data-related fields; skills in data analysis tools
Work environmentData repositories, databases, data warehousesOffice settings, data analysis software, reporting tools
Employer and industry usageUsed by data analysts, data scientists, and database managersUsed by business teams, data analysts, and decision-makers
Common search and comparison intentUnderstanding data sources and structuresInterpreting data, generating reports, making decisions

Datasets are collections of raw data used as sources for analysis, while Data Analysts interpret and analyze these datasets to generate insights and support decision-making. Datasets serve as the foundational data, whereas Data Analysts apply skills to extract value from them.

What are popular job titles related to Datasets jobs in Michigan? For Datasets jobs in Michigan, the most frequently searched job titles are:
What cities in Michigan are hiring for Datasets jobs? Cities in Michigan with the most Datasets job openings:

Full-time

Posted 12 days ago


Job description

Overview:
  • Design, develop, and optimize batch and streaming data pipelines using Spark, PySpark, Databricks, and AWS Glue.
  • Architect and maintain data lakes and warehouses (Snowflake, Redshift) and implement dbt-based data modeling for analytics-ready datasets.
  • Build and manage orchestration workflows using Apache Airflow, and automate deployments with CI/CD pipelines (GitHub Actions, Terraform, Jenkins).
  • Implement data governance, security, and compliance controls, including PII masking, RBAC, and encryption.
  • Collaborate with cross-functional teams (product managers, analysts, data scientists) to deliver datasets powering BI dashboards and ML models.
  • Optimize Spark jobs and SQL queries for performance and cost efficiency on large-scale datasets (billions of rows).
  • Develop containerized solutions using Docker and Kubernetes, ensuring high availability and scalability.
  • Monitor and troubleshoot pipelines using CloudWatch, Splunk, and Azure Monitor to maintain SLA compliance.