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Map Reduce

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Map Reduce
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Amit, Map Reduce Developer

- 8+ year experience in building data engineering and analytics products (Big data, BI, and Cloud products) - Expertise in building Artificial intelligence and Machine learning applications. - Extensive design and development experience in AZURE, Google, and AWS Clouds. - Extensive experience in loading and analyzing large datasets with Hadoop framework (Map Reduce, HDFS, PIG and HIVE, Flume, Sqoop, SPARK, Impala), No SQL databases like Cassandra. - Extensive experience in migrating on-premise infrastructure to AWS and GCP clouds. - Intermediate English - Available ASAP

Map Reduce

Map Reduce

Apache Hadoop

Apache Hadoop

Apache Kafka

Apache Kafka

GCP (Google Cloud Platform)

GCP (Google Cloud Platform)

AWS (Amazon Web Services)

AWS (Amazon Web Services)

Marcelo B.

Marcelo B., Map Reduce Developer

- Solutions Architect with excellent knowledge in the Microsoft platform, having worked since the beginning of the career (21 years of experience) with virtually all Microsoft products. - Analysis of RFP and RFI and notices of bidding opportunities for both public (Government) and private, involving Microsoft technologies like Dynamics CRM, Dynamics AX, .NET and SQL Server - Development of projects using Machine Learning, Deep Learning and Data Analysis. - Development of Blockchain projects - Consultant background with Dynamics CRM, Dynamics AX, .NET and SQL related technologies and products on high transaction applications in small and large enterprise scenarios. - Specialties: Participated deployment of CMMI level 2. Excellent experience in development, management, configuration and troubleshooting of IT, involving all Microsoft servers, especially SQL Server, Biztalk Server, Commerce Server and SharePoint Server. Excellent knowledge in Dynamics CRM and Dynamics AX. - Fluent Portuguese - Advanced English - Available ASAP

Map Reduce

Map Reduce

Azure (Microsoft Azure)

Azure (Microsoft Azure)

Dynamics CRM

Dynamics CRM

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2
Meet Carefully Matched Map Reduce Talents
Within 1-3 days, we’ll share profiles and connect you with the right Map Reduce talents for your project. Schedule a call to meet engineers in person.
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Validate Your Choice
Bring new Map Reduce expert on board with a trial period to confirm you hire the right one. There are no termination fees or hidden costs.

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Upstaff.com was launched in 2019, addressing software service companies, startups and ISVs, increasingly varying and evolving needs for qualified software engineers

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FAQs on Map Reduce Development

What is a Map Reduce Developer? Arrow

A Map Reduce Developer is a specialist in the Map Reduce framework/language, focusing on developing applications or systems that require expertise in this particular technology.

Why should I hire a Map Reduce Developer through Upstaff.com? Arrow

Hiring through Upstaff.com gives you access to a curated pool of pre-screened Map Reduce Developers, ensuring you find the right talent quickly and efficiently.

How do I know if a Map Reduce Developer is right for my project? Arrow

If your project involves developing applications or systems that rely heavily on Map Reduce, then hiring a Map Reduce Developer would be essential.

How does the hiring process work on Upstaff.com? Arrow

Post Your Job: Provide details about your project.
Review Candidates: Access profiles of qualified Map Reduce Developers.
Interview: Evaluate candidates through interviews.
Hire: Choose the best fit for your project.

What is the cost of hiring a Map Reduce Developer? Arrow

The cost depends on factors like experience and project scope, but Upstaff.com offers competitive rates and flexible pricing options.

Can I hire Map Reduce Developers on a part-time or project-based basis? Arrow

Yes, Upstaff.com allows you to hire Map Reduce Developers on both a part-time and project-based basis, depending on your needs.

What are the qualifications of Map Reduce Developers on Upstaff.com? Arrow

All developers undergo a strict vetting process to ensure they meet our high standards of expertise and professionalism.

How do I manage a Map Reduce Developer once hired? Arrow

Upstaff.com offers tools and resources to help you manage your developer effectively, including communication platforms and project tracking tools.

What support does Upstaff.com offer during the hiring process? Arrow

Upstaff.com provides ongoing support, including help with onboarding, and expert advice to ensure you make the right hire.

Can I replace a Map Reduce Developer if they are not meeting expectations? Arrow

Yes, Upstaff.com allows you to replace a developer if they are not meeting your expectations, ensuring you get the right fit for your project.

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Table of Contents

How and where is Map Reduce used?

How and where
  • Log Analysis: Analyzing system logs to identify errors
  • Data Warehousing: Processing large datasets for business intelligence
  • Sentiment Analysis: Analyzing customer feedback to determine sentiment
  • Clickstream Analysis: Analyzing user behavior on websites
  • Recommendation Systems: Generating personalized recommendations
  • Image Processing: Analyzing and processing images at scale
  • Machine Learning: Training models on large datasets
  • Fraud Detection: Identifying fraudulent activities in financial transactions
  • Genomic Data Analysis: Processing genetic data for research
  • Social Graph Analysis: Analyzing relationships in social networks

Compare Junior, Middle, Senior, and Expert/Team Lead Map Reduce Developer roles

Seniority NameYears of experienceResponsibilities and activitiesAverage salary (USD/year)
Junior1-2 yearsResponsibilities & Activities:

  • Assist in basic Map Reduce development tasks
  • Implement code based on specifications
$50,000
Middle3-5 yearsResponsibilities & Activities:

  • Develop Map Reduce applications
  • Troubleshoot and debug code
$80,000
Senior6-8 yearsResponsibilities & Activities:

  • Lead Map Reduce projects
  • Optimize performance and scalability
$110,000
Expert/Team Lead9+ yearsResponsibilities & Activities:

  • Architect Map Reduce solutions
  • Mentor team members
$150,000

Quick Facts about Map Reduce.

Facts about
  • MapReduce was created in 2004 by Google engineers.
  • Hadoop and Apache Spark are popular projects using MapReduce.
  • The entry threshold for learning MapReduce is relatively low.
  • Hadoop is one of the most popular related technologies to MapReduce.
  • MapReduce is like the Swiss Army knife of big data processing.

TOP Map Reduce Related Technologies

Related Technologies
  1. Hadoop (Doug Cutting, 2006)
  2. Apache Spark (Matei Zaharia, 2014)
  3. Apache Flink (Apache Software Foundation, 2014)
  4. Apache Storm (Nathan Marz, 2011)

What are top Map Reduce instruments and tools?

Instruments and tools
  • Hadoop: Apache’s big elephant that crunches data
  • Apache Spark: Lightning-fast data processing engine
  • Apache Flink: Real-time stream processing power

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