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Remote Hadoop MapReduce developer in India (UTC-7)
Results-driven Data Engineer with 3+ years of experience in Big Data, Cloud, and ETL pipeline development, specializing in scalable data solutions for high-volume environments. Proficient in the Hadoop ecosystem (HDFS, Hive, Sqoop, Spark, PySpark) with strong SQL expertise for data extraction, transformation, and analysis. Skilled in cloud data engineering across AWS (S3, EMR, RDS), Google Cloud (BigQuery, Dataproc, Pub-Sub, Storage, G-Sheets), and Microsoft Azure (Azure Data Lake, Azure Data Factory, Azure SQL, Synapse Analytics). Hands-on experience with Databricks for building and orchestrating distributed data pipelines and machine learning workflows. Experienced in Snowflake for cloud data warehousing. Adept at data pipeline automation, optimization, and migration using Python, Shell scripting, and Apache Airflow (Piper) to enhance efficiency and reliability. Experienced in data validation, ingestion, and monitoring, ensuring high data integrity and performance. Strong analytical mindset with a proactive problem-solving approach, capable of mentoring junior engineers, collaborating with stakeholders, and leading Agile sprint planning to drive business impact.
Remote Hadoop MapReduce developer in India (UTC+6)
Hi there! I'm Tapish, a senior engineer with 10+ years of experience across startups and big tech (AWS, GetMega). I specialize in backend systems, ML, data engineering, and developer tools. I've led teams, built products from scratch, and worked on everything from real-time infra to Chrome extensions and AI pipelines. Let's solve something together.
Remote Hadoop MapReduce developer in India (UTC-7)
Having 5+ years of work experience in IT Industry. Handled Big Data and Data Warehousing projects with extensive with Bigdata like Apache Hadoop v2.7.1, Apache Spark,Scala,Hadoop, Apache Hive, Python, Sqoop and AWS .
Remote Hadoop MapReduce developer in India (UTC-7)
Experienced Python and Node.js developer with 5 years of expertise in backend automation, scalable system design, and AI tooling. Proven track record at Turing and American Express (via TCS) delivering prompt optimisation pipelines, data ingestion automation, and infrastructure reliability improvements. I’m passionate about building impactful AI-driven products and aspire to take on roles where I can drive both technical innovation and team leadership in AI, backend systems, and automation.
Remote Hadoop MapReduce developer in India (UTC+6)
I am a Software Developer with 5+ years of experience specializing in backend and full-stack development. Expertise in backend frameworks like Flask, Django, and FastAPI, frontend frameworks like ReactJS, as well as databases such as PostgreSQL, MS-SQL, and MongoDB. Adept at building scalable and efficient solutions for a variety of projects, including fintech applications, document-based chat systems, and cloud-based platforms. Experienced in leading cross-functional teams, working on machine learning models (LLMs, LangChain), and implementing cloud-based solutions on AWS, GCP, and Azure.
Vetted Hadoop MapReduce developer in India (UTC+6)
Experienced Software Engineer with a demonstrated history of working in the internet industry. Skilled in Java, NoSQL, SQL, Quartz, and Spring Framework, AWS Technologies. Strong engineering professional with a Bachelor of Technology (B.Tech.) focused on Computer Science & Engineering from Bundelkhand Institute of Engineering and Technology. Apart from teamwork, have been involved in reviewing threat model suggesting mitigations for different teams.
Vetted Hadoop MapReduce developer in India (UTC-7)
I am an accomplished engineering leader with 20+ years in Fintech, Travel, and e-Commerce. I excel in cross-cultural team leadership, rapid product launches, and scaling for hyper-growth. My career spans pivotal roles at ThoughtWorks, Cleartrip, SAP-Ariba, and Simpl. I lead strategic roadmaps and cloud-native solutions at Simpl and Cleartrip, specializing in real-time data processing and machine learning. At Simpl, I reduced processing times to 60 milliseconds, boosting user approval and TPV. At Cleartrip, I enhanced a data platform, increasing conversions by 0.75% and implementing advanced analytics. I optimized AWS costs by 13%, improved search efficiency by 80%, and managed a monitoring system handling millions of documents with 15-millisecond latency. I also streamlined Cleartrip’s release cycles to weekly, implementing agile CI/CD practices with a 15-minute build cycle. I thrive on designing and architecting platforms, solutions, and productivity tools. My journey into distributed systems since 2015 has fueled my curiosity and love for exploring white papers and books on the subject. I enjoy programming, problem-solving, and collaborating with like-minded individuals. Deeply engaged in the tech community, I attend meet-ups to discuss cutting-edge topics in distributed systems and language advancements, while currently focusing on mastering MLOps principles for deploying machine learning models effectively. I have extensive SaaS product experience, contributing to Mingle, an agile project management tool, and Twist, a BDD test automation tool, at ThoughtWorks Studios. At SAP, I developed SAP Logistics Business Network and SAP Business Network Freight Collaboration, leading the engineering team to design scalable features for intercompany logistics collaboration, optimize cloud deployment for global accessibility, and enhance the user interface for managing logistics operations. Beyond work commitments, I find joy in photography, birdwatching, swimming, cycling, yoga, and bodyweight exercises. I am also an enthusiastic trekker, having explored extensive regions of the Western Ghats. Reach out to me to explore consulting opportunities, discuss engineering challenges, or exchange insights on technology and entrepreneurship. I'm open to talking about; - Hiring and Building Product Engineering Teams - Provided mentorship to build high-quality engineering teams for product companies, fostering growth and development within the team. - Product Development - Data Engineering Platform and MLOps capabilities - Strategic Leadership
Vetted Hadoop MapReduce developer in India (UTC+6)
Experienced Software Development Engineer with strong expertise in backend system architecture design for distributed systems. Good understanding and exposure to multiple architectural design patterns for designing scalable performant systems. Hands on experience with multiple AWS cloud services. Experienced Big Data Engineer for architecting and designing ETL pipelines for processing large data and delivering valuable insights. Optimizing Spark jobs for faster processing. Strong knowledge and hands on with Microservices with Dockers and Kubernetes.
Vetted Hadoop MapReduce developer in India (UTC+6)
* Experienced in leveraging AWS technologies (Lambda, EC2, Beanstalk, DynamoDB, RDS, EMR, S3, SQS, etc) and opensource technologies like Cassandra, RabbitMQ, etc to solve problems and develop solutions. * I also have experience with various data science and quant libraries like numpy, pandas, scipy, quantlib, pinescript, etc. * I am someone who is empathetic, patient but a go-getter who likes to learn by doing and hacking. * I hold myself to high standards of a software professional. This means that I am committed to: write the best code I can produce in the scope of the project, accountability, responsiveness, and setting clear expectations.
Vetted Hadoop MapReduce developer in India (UTC+6)
Senior QA Automation Lead Engineer with 8 years of proven expertise in designing and implementing scalable test automation frameworks and CI/CD pipelines for distributed containerized cloud-based environments and for Intel’s innovative Developer Toolbox for Edge-AI. Increased test automation coverage by 67% for both frontend and backend applications, reducing manual testing effort and enabling faster release cycles. Proven leadership in guiding teams to achieve 95% end-to-end test automation, streamlining and optimizing testing and DevOps processes and enhancing software quality and reliability.
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Get startedArc offers pre-vetted remote developers skilled in every programming language, framework, and technology. Look through our popular remote developer specializations below.
Arc helps you build your team with our network of full-time and freelance Hadoop MapReduce developers worldwide.
We assist you in assembling your ideal team of programmers in your preferred location and timezone.
In today’s world, most companies have code-based needs that require developers to help build and maintain. For instance, if your business has a website or an app, you’ll need to keep it updated to ensure you continue to provide positive user experiences. At times, you may even need to revamp your website or app. This is where hiring a developer becomes crucial.
Depending on the stage and scale of your product and services, you may need to hire a Hadoop MapReduce developer, multiple engineers, or even a full remote developer team to help keep your business running. If you’re a startup or a company running a website, your product will likely grow out of its original skeletal structure. Hiring full-time remote Hadoop MapReduce developers can help keep your website up-to-date.
To hire a Hadoop MapReduce developer, you need to go through a hiring process of defining your needs, posting a job description, screening resumes, conducting interviews, testing candidates’ skills, checking references, and making an offer.
Arc offers three services to help you hire Hadoop MapReduce developers effectively and efficiently. Hire full-time Hadoop MapReduce developers from a vetted candidates pool, with new options every two weeks, and pay through prepaid packages or per hire. Alternatively, hire the top 2.3% of expert freelance Hadoop MapReduce developers in 72 hours, with weekly payments.
If you’re not ready to commit to the paid plans, our free job posting service is for you. By posting your job on Arc, you can reach up to 450,000 developers around the world. With that said, the free plan will not give you access to pre-vetted Hadoop MapReduce developers.
Furthermore, we’ve partnered with compliance and payroll platforms Deel and Remote to make paperwork and hiring across borders easier. This way, you can focus on finding the right Hadoop MapReduce developers for your company, and let Arc handle the logistics.
There are two types of platforms you can hire Hadoop MapReduce developers from: general and niche marketplaces. General platforms like Upwork, Fiverr, and Gigster offer a variety of non-vetted talents unlimited to developers. While you can find Hadoop MapReduce developers on general platforms, top tech talents generally avoid general marketplaces in order to escape bidding wars.
If you’re looking to hire the best remote Hadoop MapReduce developers, consider niche platforms like Arc that naturally attract and carefully vet their Hadoop MapReduce developers for hire. This way, you’ll save time and related hiring costs by only interviewing the most suitable remote Hadoop MapReduce developers.
Some factors to consider when you hire Hadoop MapReduce developers include the platform’s specialty, developer’s geographical location, and the service’s customer support. Depending on your hiring budget, you may also want to compare the pricing and fee structure.
Make sure to list out all of the important factors when you compare and decide on which remote developer job board and platform to use to find Hadoop MapReduce developers for hire.
Writing a good Hadoop MapReduce developer job description is crucial in helping you hire Hadoop MapReduce developers that your company needs. A job description’s key elements include a clear job title, a brief company overview, a summary of the role, the required duties and responsibilities, and necessary and preferred experience. To attract top talent, it's also helpful to list other perks and benefits, such as flexible hours and health coverage.
Crafting a compelling job title is critical as it's the first thing that job seekers see. It should offer enough information to grab their attention and include details on the seniority level, type, and area or sub-field of the position.
Your company description should succinctly outline what makes your company unique to compete with other potential employers. The role summary for your remote Hadoop MapReduce developer should be concise and read like an elevator pitch for the position, while the duties and responsibilities should be outlined using bullet points that cover daily activities, tech stacks, tools, and processes used.
For a comprehensive guide on how to write an attractive job description to help you hire Hadoop MapReduce developers, read our Engineer Job Description Guide & Templates.
The top five technical skills Hadoop MapReduce developers should possess include proficiency in programming languages, understanding data structures and algorithms, experience with databases, familiarity with version control systems, and knowledge of testing and debugging.
Meanwhile, the top five soft skills are communication, problem-solving, time management, attention to detail, and adaptability. Effective communication is essential for coordinating with clients and team members, while problem-solving skills enable Hadoop MapReduce developers to analyze issues and come up with effective solutions. Time management skills are important to ensure projects are completed on schedule, while attention to detail helps to catch and correct issues before they become bigger problems. Finally, adaptability is crucial for Hadoop MapReduce developers to keep up with evolving technology and requirements.
You can find a variety of Hadoop MapReduce developers for hire on Arc! At Arc, you can hire on a freelance, full-time, part-time, or contract-to-hire basis. For freelance Hadoop MapReduce developers, Arc matches you with the right senior developer in roughly 72 hours. As for full-time remote Hadoop MapReduce developers for hire, you can expect to make a successful hire in 14 days. To extend a freelance engagement to a full-time hire, a contract-to-hire fee will apply.
In addition to a variety of engagement types, Arc also offers a wide range of developers located in different geographical locations, such as Latin America and Eastern Europe. Depending on your needs, Arc offers a global network of skilled engineers in various different time zones and countries for you to choose from.
Lastly, our remote-ready Hadoop MapReduce developers for hire are all mid-level and senior-level professionals. They are ready to start coding straight away, anytime, anywhere.
Arc is trusted by hundreds of startups and tech companies around the world, and we’ve matched thousands of skilled Hadoop MapReduce developers with both freelance and full-time jobs. We’ve successfully helped Silicon Valley startups and larger tech companies like Spotify and Automattic hire Hadoop MapReduce developers.
Every Hadoop MapReduce developer for hire in our network goes through a vetting process to verify their communication abilities, remote work readiness, and technical skills. Additionally, HireAI, our GPT-4-powered AI recruiter, enables you to get instant candidate matches without searching and screening.
Not only can you expect to find the most qualified Hadoop MapReduce developer on Arc, but you can also count on your account manager and the support team to make each hire a success. Enjoy a streamlined hiring experience with Arc, where we provide you with the developer you need, and take care of the logistics so you don’t need to.
Arc has a rigorous and transparent vetting process for all types of developers. To become a vetted Hadoop MapReduce developer for hire on Arc, developers must pass a profile screening, complete a behavioral interview, and pass a technical interview or pair programming.
While Arc has a strict vetting process for its verified Hadoop MapReduce developers, if you’re using Arc’s free job posting plan, you will only have access to non-vetted developers. If you’re using Arc to hire Hadoop MapReduce developers, you can rest assured that all remote Hadoop MapReduce developers have been thoroughly vetted for the high-caliber communication and technical skills you need in a successful hire.
Arc pre-screens all of our remote Hadoop MapReduce developers before we present them to you. As such, all the remote Hadoop MapReduce developers you see on your Arc dashboard are interview-ready candidates who make up the top 2% of applicants who pass our technical and communication assessment. You can expect the interview process to happen within days of posting your jobs to 450,000 candidates. You can also expect to hire a freelance Hadoop MapReduce developer in 72 hours, or find a full-time Hadoop MapReduce developer that fits your company’s needs in 14 days.
Here’s a quote from Philip, the Director of Engineering at Chegg:
“The biggest advantage and benefit of working with Arc is the tremendous reduction in time spent sourcing quality candidates. We’re able to identify the talent in a matter of days.”
Find out more about how Arc successfully helped our partners in hiring remote Hadoop MapReduce developers.
Depending on the freelance developer job board you use, freelance remote Hadoop MapReduce developers' hourly rates can vary drastically. For instance, if you're looking on general marketplaces like Upwork and Fiverr, you can find Hadoop MapReduce developers for hire at as low as $10 per hour. However, high-quality freelance developers often avoid general freelance platforms like Fiverr to avoid the bidding wars.
When you hire Hadoop MapReduce developers through Arc, they typically charge between $60-100+/hour (USD). To get a better understanding of contract costs, check out our freelance developer rate explorer.
According to the U.S. Bureau of Labor Statistics, the medium annual wage for developers in the U.S. was $120,730 in May 2021. What this amounts to is around $70-100 per hour. Note that this does not include the direct cost of hiring, which totals to about $4000 per new recruit, according to Glassdoor.
Your remote Hadoop MapReduce developer’s annual salary may differ dramatically depending on their years of experience, related technical skills, education, and country of residence. For instance, if the developer is located in Eastern Europe or Latin America, the hourly rate for developers will be around $75-95 per hour.
For more frequently asked questions on hiring Hadoop MapReduce developers, check out our FAQs page.