Enterprise Solutions, Inc.
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https://www.enterprisesolutioninc.com
https://www.enterprisesolutioninc.com
USD
60
80
HOUR
true
Job description
Big Data Architect
Warren, NJ 07059 United States
Posted: 10/11/2024
2024-10-11
2025-01-07
Job Number: z5G7h3l6a1kMvyS65NP3c6EsNcIKV9H_uUKEUY9AS7o=
Pay Rate: 60-80 Hourly USD
Job Description
Job description
- The candidate should be able to perform data analysis using sql queries
- Create data models on big data platform like Hadoop optionally on Snowflake
- Hand on development experience with industry leading ETL or Reporting tool
- Develop implement and maintain leading edge analytic systems taking complicated problems and building simple frameworks
- Identify trends and opportunities for growth through analysis of complex data sets
- Evaluate organizational methods and provide source to target mappings and information model specification documents for data sets
- Evaluate internal systems for efficiency problems and inaccuracies developing and maintaining protocols for handling processing and cleaning data
- Work directly with management and users to gather requirements provide status updates and build relationships
- Work closely with management to understand and maintain focus on their analytical needs including identifying critical metrics and KPIs and deliver actionable insights to relevant decisionmakers
- Proactively analyze data to answer key questions from stakeholders or out of self-initiated curiosity with an eye for what drives business performance investigating and communicating areas for improvement in efficiency and productivity
- Create and maintain rich interactive visualizations through data interpretation and analysis integrating various reporting components from multiple data sources
- Define and implement data acquisition and integration logic selecting appropriate combination of methods and tools within defined technology stack to ensure optimal scalability and performance of the solution
- Develop and maintain databases by acquiring data from primary and secondary sources and build scripts that will make our data evaluation process more flexible or scalable across data sets
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