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Recently Added Hadoop Developers in our Network

Jyoti ranjan pattnaik

Jyoti ranjan pattnaikProfile Badge IC

Senior Associate (AVP, Software Engineer 3)13.3 Years of Exp
  • Data Warehousing
  • SQL
  • AWS
  • Data Engineering
  • Big Data
  • Apache Spark
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I work as Associate in JP Morgan & Chase in Mumbai, India. I hold a Bachelor’s degree in Computer Science from ITER, SOA university, Bhubaneswar, Odisha, India.I have worked for more than 13 years as a Software Developer in FinTech and Telecom. In JPMC, I work as Tech Lead with extensive experience in designing and implementing scalable, high-performance systems. I hold deep expertise in AWS, Apache Spark, Kafka, Big Data technologies, and Java. With a proven track record in designing the most efficient software solutions, I excel in leading teams to tackle complex problems and deliver impactful results. My passion for problem-solving drives me to continuously innovate and optimize systems, ensuring they meet the highest standards of performance and reliability. I am dedicated to staying at the forefront of technology trends and applying best practices in cloud computing, data processing, and software development.

Kaushik Sharma

Kaushik SharmaProfile Badge IC

Senior Associate Data Engineering L19 Years of Exp
  • Agile Methodology
  • Analytical Skills
  • Communication Skills
  • View all (5)

Senior Data Engineer, proficient in designing and developing DataPipeline, deliver Data Integration, Governance and Wrangling solutions. Tech Evangelist with great analytical and logical skills, possessing work experience of overseeing the facets of Big Data platform setup, expansion, and maintenance. Expert in heading the deliveries and experienced in full stack Big Data development using various Big Data tools.

Piyush Mishra

Piyush MishraProfile Badge IC

Senior Data Engineer9 Years of Exp
  • Data Analysis
  • data-science
  • Data Warehousing
  • ETL
  • Agile Scrum
  • View all (8)

8.4 years of diverse experience in Data Engineering field, including Development, and Implementation of various applications in big data and EDW environments.

Rajagopal Bojanapalli

Rajagopal BojanapalliProfile Badge IC

Software Engineer10 Years of Exp

With over a decade of experience in the field, I have honed my skills in MySQL, Java, Python, and Hadoop to a high level of proficiency. My expertise in these technologies has enabled me to successfully tackle a wide range of projects and challenges throughout my career. From designing and optimizing databases to developing complex software solutions, I have demonstrated a strong ability to deliver results and drive innovation. My extensive experience has equipped me with the knowledge and skills necessary to excel in the ever-evolving world of technology.

Ramakrishna Kota

Ramakrishna KotaProfile Badge IC

Senior Data Engineer14 Years of Exp
  • Java
  • Python
  • machine_learning
  • Data Processing
  • Hadoop
  • Kubernetes
  • View all (9)

GoogleCloudCertified Data Engineer with a demonstrated history of working in the software development and Big data technologies . Skilled in Apache Spark, Cloudera,Flink,Core Java, Hadoop, noSQLDBs. and have experience with cloud-based big data platforms such as GCP and AWS.

Rohan Jethure

Rohan JethureProfile Badge IC

Senior Associate Technology7.5 Years of Exp

Big Data Developer• Total experience: 8+ years of experience in software design and development with Hadoop, Spark, Scala, Microsoft Azure (Eventhub, Azure HDInsight, Azure AppInsight, Key-vault, BlobStorage, Cosmos DB), Jenkins, Hive• Experience in building low latency data pipeline using spark streaming• Worked on various phases of Product Development Life Cycle in variety of technical areas like design, development, production Support.• Worked in programming languages - Java, Scala and shell scripting.• Worked on ETL side to extract, transform, load data.• Worked on GIT Repository to maintain the code.• Explored the Azure services like Appinsight, key-vault, Blob Storage, Cosmos DB, Eventhubs• To ingest the data from source eventhub using Spark-Scala• Transform the ingested data and Store the output data to Target cosmosDB and update the checkpoint location to Azure Blob-storage• Validated the data from target eventhub and debugging the code.• Run the Streaming job on Azure HDinsight cluster.• Have done unit testing by writing test cases.• Have done code coverage on sonarquebe.• Have done code review on GIT while sending merge request.

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Uplers helped to source and bring out the top talent in India, any kind of high-level role requirement in terms of skills is always sourced based on the job description we share. The profiles of highly vetted experts were received within a couple of days. It has been credible in terms of scaling our team out of India.

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Hire Hadoop Engineers to Discover Scalable and Efficient Big Data Solutions

A professional data strategy has become the hallmark of success in the modern business world across sectors. Organizations today deal with large amounts of data. This necessitates the utilization of the right tools and talent to manage and optimize such massive data opportunities.

Frequently Asked Questions

Uplers provides AI-vetted talent, ensuring a seamless hiring experience. Our efficient process ensures profile shortlisting within 48 hours, allowing you to swiftly onboard qualified professionals within just 2 weeks. Additionally, we prioritize client satisfaction with our flexible terms, including a 30-day cancellation policy and a lifetime free replacement.

You can get the top 3.5% of AI-vetted profiles in less than 48 hours through Uplers. Once you finalize one of the most suitable Hadoop Developers, Uplers takes care of the entire hiring and onboarding formalities. This typically takes 2-4 weeks depending on your requirements and decision-making time.

The modes of communication through which you can get in touch with a hired Hadoop Developer include:

  • Email
  • Phone
  • Messaging apps such as WhatsApp, Slack, or Microsoft Teams

Uplers offers a 30-day cancellation policy at no extra cost and lifetime free replacement.

The average cost of hiring a Hadoop Developer from Uplers starts at $2500. The number varies depending on the experience level of the developer as well as your requirements.

View Our Pricing For 2024 - 25

At Uplers, our screening process ensures a thorough evaluation of candidates' language proficiency, facilitated by our AI-vetting technology. Beyond linguistic skills, we prioritize cultural fitness to ensure seamless integration within your team, fostering a harmonious work environment and seamless collaboration.

Yes, Hadoop developers are still in demand, especially for big data processing in enterprises. While newer technologies have emerged, Hadoop remains crucial for large-scale data storage, batch processing, and analytics in industries like finance, healthcare, and telecom.

Hadoop developers are focusing on cloud integration, real-time analytics, and AI-driven data processing. Trends include migrating Hadoop workloads to cloud platforms, integrating with Apache Spark for faster processing, leveraging Hadoop with AI/ML pipelines, and enhancing security and scalability for big data applications.

For urgent roles, Uplers:

  • Provides vetted profiles within 3-4 business days
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  • Offers express hiring options for immediate deployment

This minimizes hiring delays and ensures quick project execution.

Uplers ensures quality through:

  • A 5-step vetting process (technical screening, AI-driven assessments, communication tests, cultural fit analysis, and final review)
  • Live coding assessments for development roles
  • Performance tracking for ongoing engagements

This guarantees top-tier talent that meets business needs.

Pricing is based on:

  • Candidate's skill level & experience
  • Full-time vs. part-time vs. project-based hiring
  • Market benchmarks to ensure fair pay

Uplers provides transparent pricing with customizable engagement models.

Uplers minimizes risks through:

  • 14 to 30-day replacement guarantees
  • Flexible exit clauses in hiring contracts
  • Continuous candidate performance tracking

This ensures high retention and reduced hiring failures.