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Recently Added Hadoop Developers in our Network

Jyoti ranjan pattnaik

Senior Associate (AVP, Software Engineer 3)Exp. 13.3 Years
  • Data Warehousing
  • SQL
  • AWS
  • Data Engineering
  • Big Data
  • Apache Spark
  • Big Data Technologies
  • Git
  • Java

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

Senior Data EngineerExp. 8 Years
  • Java
  • Ubuntu
  • HTML
  • Python
  • Agile
  • C
  • C++
  • Scala
  • Windows
  • DevOps
  • Big Data
  • Data Engineering

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

Senior Data EngineerExp. 9 Years
  • Data Analysis
  • Data Science
  • Data Warehousing
  • ETL
  • Agile/Scrum
  • Data Modeling
  • Data Engineering
  • Python

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

Software EngineerExp. 10 Years
  • MySQL
  • Java
  • Python
  • Hadoop
  • Apache Spark
  • GCP
  • Elasticsearch
  • Kubernetes
  • Pyspark
  • Terraform

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.

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Various Skills that Hadoop Developers Possess

Access the talent network of 1.5M+ skilled professionals with 100+ skill sets

  • HDFS
  • MapReduce
  • YARN
  • Hive
  • Pig
  • HBase
  • Sqoop
  • Flume
  • Java
  • Python
  • Scala
  • Apache Spark
  • Apache Storm
  • Apache Flink
  • Apache Kafka
  • Talend
  • Informatica
  • Parquet
  • ORC
  • Avro
  • JSON
  • CSV/TSV
  • Gzip
  • Zip
  • Apache Drill
  • Apache Impala
  • Presto
  • Ambari
  • Cloudera Manager
  • Kerberos
  • Zookeeper
  • Amazon EMR
  • Google Cloud Dataproc
  • Microsoft Azure HDInsight
  • Git
  • Jenkins
  • Apache Mahout
  • TensorFlow
  • Docker
  • Kubernetes
  • Bash scripting
  • Shell scripting
  • Oozie

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Case Study

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Hire a top talent

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.

This is where Hadoop comes into significance. It is an efficient open-source framework that is used for storing, managing, and analyzing big data.

Hadoop gives an unparalleled degree of scalability along with cost-effectiveness. To make the best use of Hadoop, businesses prefer a Hadoop developer for hire who understands the complexity of this system. In this guide, we explain why organizations hire Hadoop engineers to ensure success in data strategies and profitable business outcomes.

  1. Understanding Hadoop's Role in Data Strategy

    Hadoop represents the core of current big data strategies. It offers a framework that can process large datasets. Its architecture has been designed to scale across clusters of data and organizations. This makes Hadoop ideal for managing data at an enterprise level. The Hadoop ecosystem consists of technicalities like:

    • HDFS or Hadoop Distributed File System, which offers scalable and fault-tolerant data storage.

    • MapReduce allows efficient data processing through distributed computing.

    • YARN or Yet Another Resource Negotiator, manages the resources of the cluster and schedules tasks.

    • Apache Hive is used for querying data, Apache Pig for scripting, and Apache Spark for real-time data processing.

  2. The Value of Hiring Skilled Hadoop Developers

    Experienced Hadoop developers have plenty of rich skills and significant advantages like:

    Handling a Mass Amount of Data

    Hadoop developers work on huge applications, design or implement petabytes or even more data at any given moment, and work on producing such architectures. All this translates to efficient and robust processes for the reliable processing of big volumes of data.

    Implementing Scalable and Cost-Effective Data Solutions

    Hadoop's architecture is distributed so businesses can scale their data infrastructure effortlessly. Skilled developers can develop systems that are built to scale at an optimized cost.

    Integrating with Existing Data Infrastructure

    A professional Hadoop developer can integrate Hadoop with current systems – relational databases or cloud platforms so that there is a unified data ecosystem.

  3. Key Skills to Look for in Hadoop Developers

    Before you hire Hadoop developers, check their technical and analytical skills:

    Proficiency in Hadoop Ecosystem Components

    An expert Hadoop developer should understand the core parts of the Hadoop ecosystem components, which include HDFS, MapReduce, YARN, Hive and Pig, and Apache Spark. Such skills guarantee the developer's capability of designing, implementing, and optimizing data solutions.

    Experience with Programming Languages

    A Hadoop developer should know one or more of the following programming languages:

    • Java - The primary contender for developing Hadoop is the development of Java. It is also used for writing programs for MapReduce operations and working with Hadoop APIs.
    • Python - Used for simplicity and versatility, mainly in data manipulation, scripting, and integration works.
    • Scala - Used for development with Apache Spark and large-scale data processing.
    Data Modeling and ETL Expertise

    Hadoop developers should have a strong grasp of:

    • Data Modeling - Creating schemas and structures for efficient storage and retrieval of large datasets.
    • ETL Processes - Skills in applying Extract, Transform, and Load methods for smooth data integration and transformation from different sources.
    • Data Pipeline Development - Ability to design automated pipelines that help efficiently process data while keeping the data quality intact.
    Knowledge of Real-Time Data Processing

    Organizations hire Hadoop engineers to process and analyze real-time data. The professionals should be able to:

    • Use tools like Apache Spark Streaming, Apache Flink, or Kafka to handle streaming data.
    • Design systems that give near-real-time insights for dynamic business decisions.
    • Design and optimize workflows for the least amount of latency with maximum efficiency in real-time data environments.
  4. Business Outcome Impact of Hadoop Expertise

    Beyond technical implementation, expert Hadoop developers provide many benefits in business outcome realization.

    More Data Processing Capability

    Through Hadoop's distributed computing, businesses can process huge amounts of data quickly, leading to more effective and precise decision-making.

    Effective Storage Solution

    The low-cost storage offered by Hadoop provides a guarantee for the growth of business data with accessibility and performance without loss of data.

    Advanced Analytics and Machine Learning

    With Hadoop's seamless integration capabilities, businesses can work on advanced analytics and machine learning, creating new areas of innovation and growth.

  5. Conclusion

    Businesses today hire Hadoop developers for their excellent data strategies. Their technical acumen and strategic vision help organizations explore the full potential of big data, which drives efficiency, innovation, and growth.

    AI-powered hiring platforms like Uplers simplify the process of hiring top-tier Hadoop developers. With global access to hundreds of thousands of tech talent profiles, Uplers guarantees that any business can put together the right team to achieve its data strategy goals.

FAQs

Why should you choose Uplers for hiring Hadoop Developers?

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.

How quickly can I hire a Hadoop developer through Uplers?

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.

What are the modes of communication through which we can get in touch with a hired Hadoop Developer?

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

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

What if I am not okay with the Hired Hadoop Developers and would like to change the resources or end the engagement?

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

What is the average cost of hiring experienced remote Hadoop Developers?

The average cost of hiring a Hadoop Developer from Uplers starts at $1500. The number varies depending on the experience level of the developer as well as your requirements.

Can I expect absolute English proficiency for the Hadoop Developer hired through Uplers?

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.

Are Hadoop Developers still in demand?

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.

What are the latest trends in Hadoop Developers?

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.

How does Uplers handle candidate availability for urgent hiring needs?

For urgent roles, Uplers:

  • Provides vetted profiles within 3-4 business days
  • Has a pre-vetted talent network of 1M+ professionals
  • Offers express hiring options for immediate deployment

This minimizes hiring delays and ensures quick project execution.

How does Uplers ensure quality control in hiring for product companies?

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.

How does Uplers structure pricing for SaaS hiring?

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.

How does Uplers reduce hiring risks for SaaS and tech companies?

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.