Barry Petersen

Senior Database Developer at Michael Page

Based in Brooklyn, United States

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Seniority

Staff

Department

Information Technology

Location

Brooklyn

Industry

Staffing and Recruiting

Company size

13K

Contact information

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Email

1 credit

b•••••••@page.com

Phone

5 credits

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Background

About Barry Petersen

Passionate Senior Data Engineer with 15+ years of experience designing, optimizing, and migrating enterprise data platforms. Proven ability to build scalable data pipelines, lead cloud transformations, and optimize ETL workflows for high-impact business intelligence. I specialize in Azure, Databricks, Power BI, and SQL, delivering data-driven insights that empower organizations to make strategic decisions. Whether it's enhancing financial forecasting, improving operational efficiency, or streamlining reporting, I bring a solutions-oriented mindset to every project. Key Expertise: Data Engineering | ETL Pipelines | Cloud Migrations (Azure, AWS, GCP) Power BI | SQL (Postgres, Redshift, MySQL)| Python | Spark | Databricks AI & Machine Learning Integration for Business Intelligence Process Optimization | Data Governance | Real-Time Data Streaming Currently seeking senior leadership opportunities where I can drive enterprise-wide data strategies, mentor teams, and implement AI-driven solutions. Open to networking and knowledge-sharing—let’s connect! Work experience section should look like this: Senior Database Developer → Senior Data Engineer PageGroup | December 2007 – Present (17 years) Summary: Led enterprise-wide data engineering initiatives, modernizing reporting systems, migrating on-prem data to Azure Cloud, and implementing AI-powered big data solutions. Designed ETL workflows that improved data refresh efficiency by 40% and reduced infrastructure costs. Key Achievements: Migrated SSRS reports to Power BI & Azure Data Factory, improving reporting automation and reducing manual reporting by 50%. Built ETL pipelines for real-time data processing, optimizing transaction tracking for 800+ active users. Developed financial data models, increasing forecasting accuracy by 20%. Led cross-functional collaboration with data scientists, analysts, and IT teams to streamline CRM data pipelines.

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