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137 Remote Spark dataframe developers and experts available to hire:

Spark dataframe developers in Brazil - hugo A.
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hugo A.

Vetted Spark dataframe developer in Brazil (UTC-3)

**Deep Learning Architect (L5) | AWS Generative AI Innovation Center** _São Paulo, Brazil_ With 5+ years experience in AI/ML, I am currently a Deep Learning Architect at AWS Generative AI Innovation Center, blending my expertise in Generative AI science with advanced architectural design to deliver robust, scalable solutions. In my role, which merges the responsibilities of a Data Scientist and a Solutions Architect, I lead customer engagements from proof-of-concept to production-grade systems, ensuring they are secure, fault-tolerant, and optimized for enterprise performance. As a tech lead, I maintain a hands-on approach—contributing to model development, optimization, and deployment—while collaborating with diverse teams to design solutions that drive innovation and disrupt industries. I am seeking long-term opportunities where I can leverage my dual expertise to develop cutting-edge Generative AI solutions and help companies revolutionize their business verticals through transformative technology. ### **Technical Skills** **Artificial Intelligence & Machine Learning** * Expertise in Large Language Models (LLMs), Natural Language Processing (NLP), Computer Vision, Neural Networks, Transformers * Hands-on experience with frameworks: PyTorch, TensorFlow, Scikit-learn **Cloud Computing & DevOps** * 4 AWS Certified (Soultions Architect, Cloud Developer, Machine Learning Specialty, Data Analytics Specialty), Docker, Kubernetes, CircleCI, Elastic Beanstalk, Apache Airflow **Programming & Software Development** * Proficient in Python, R, and SQL * Experienced in building and consuming RESTful APIs and GraphQL **Data Engineering & Big Data** * Skilled in Apache Spark, NoSQL databases (MongoDB, DynamoDB, Elasticsearch) * Experienced in building data pipelines, ETL processes, and optimizing data workflows **Data Analytics & Visualization** * Proficient in Power BI * Proficient Plotly, Bokeh, Matplotlib and Seaborn * Advanced statistical modeling using using R and statsmodels **Soft Skills** * Strong problem-solving ability, Agile/Scrum methodology, proven team leadership, and commitment to continuous learning **Languages** * Portuguese (Native), English (Fluent), French (Fluent), Spanish (Advanced), German (Advanced)

Spark dataframe developers in Brazil - Igor T.
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Igor T.

Vetted Spark dataframe developer in Brazil (UTC-3)

I am a Software Engineer who has been working with data since 2017. In my career, I have worked on different solutions, such as planning and building a Data Lake on AWS using Delta Lake to store 3D Printer sensor information, and developing a data product to device the optimal energy allocation in Minning facilities reducing the cost of R$1,000,000.00 per year using R. My primary programming language is Python, and I have expertise working with data engineering tools in the AWS environment, like Spark, Airflow, Redshift, EMR, Kinesis, and Lambda. My greatest passion is working with projects that can challenge me and make me a better developer

Spark dataframe developers in Brazil - Aniceto J.
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Aniceto J.

Vetted Spark dataframe developer in Brazil (UTC-3)

I am a data engineer and Backend Developer with more than 15 years of experience in software development and systems analysis. I have a bachelor's degree in Information System, a master's degree in Computer Science and a PhD in Mechanical Engineering with an emphasis on artificial intelligence. In the first quarter of 2020, finalize a data lake project on AWS to receive data from the industrial sector. I work with technologies such as AWS, Docker, Kubernetes, Java, AngularJS, Angular 8, Python, NodeJS, SpringBoot, PostgreSQL, SQL Server, MYSQL. I have the ability to learn and integrate different technologies.

Spark dataframe developers in Brazil - Tiago F.
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Tiago F.

Vetted Spark dataframe developer in Brazil (UTC-3)

Results-driven data engineer with 6 years of experience in designing and implementing data solutions. Proficient in leveraging PySpark, Python, Hadoop, PostgreSQL, and AWS to develop scalable and efficient data pipelines, ETL processes, and data warehousing solutions. Demonstrated expertise in optimizing data workflows, ensuring data quality and integrity, and driving data-driven decision-making. Adept at collaborating with cross-functional teams to deliver innovative solutions that meet business requirements. Strong problem-solving and analytical skills combined with a commitment to continuous learning and staying up-to-date with emerging technologies in the data engineering space.

Spark dataframe developers in Brazil - Caio S.
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Caio S.

Vetted Spark dataframe developer in Brazil (UTC-3)

As a data engineer I'm driven by solving problems with the most clean and efficient solution, I am passionate about working with data in many different levels. With experience from collecting data all the way to creating dashboards and drawing insights I can reliably take in consideration the wider scope of any process do design and implement data driven solutions.

Spark dataframe developers in Brazil - Matheus Z.
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Matheus Z.

Vetted Spark dataframe developer in Brazil (UTC-3)

Hello, my name is Matheus and I am a full stack developer with experience in the finance industry. I have more than 5 years of experience in developing and maintaining backend systems for financial institutions using Node.js and TypeScript. I have experience in building and deploying high-performance and scalable servers utilizing modern Javascript language features. I am familiar with popular Node.js frameworks such as Express.js, Nest.js and well-versed in Object-oriented concepts and design patterns that help me to structure and maintain my codebase. Also, I have experience with database technologies like MySQL, MongoDB and well-versed in version control systems like git.

Spark dataframe developers in Brazil - Felippe M.
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Felippe M.

Vetted Spark dataframe developer in Brazil (UTC-3)

I'm an Engineer, with a background in Artificial Intelligence, and I've always sought to use technology to solve problems. In my Master's, my study focused on Artificial Neural Networks, and I've published scientific articles and produced a dissertation on the subject. In the last four years, I've dedicated myself to studying Data Science (Python, ML, SQL, Spark). I'm responsible and a team worker. During my career, I've taken on several managerial roles, having even led remote teams. I know how to work with other people and try to treat everyone with respect and courtesy. I'm always open to hearing suggestions, criticisms, and other perspectives. I have just finished the Data Science Bootcamp with the french school Le Wagon. It was an amazing experience and I was able to further consolidate my skills in Data Science: statistics and probability, SQL, Python (Pandas, Numpy, Sklearn, PyTorch, Tensorflow/Keras), NLP, MLOPs basics (Google Cloud). I am searching for new challenges and experiences, and I believe I can make valuable contributions.

Spark dataframe developers in Brazil - Lawrence F.
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Lawrence F.

Vetted Spark dataframe developer in Brazil (UTC-3)

I'm a Data architect, with past experiences in Business Intelligence and Data Engineering on leading companies, such as IBM, B2W, and Nestlé. I've being working for 5 years on Big Data projects, using multiple clouds (GCP, AWS, and Azure) and architectures (Data Warehouses/Lakes/Lakehouses, Modern Data Platforms, Data Mesh). Currently, I'm the leader of Debussy, an opinionated open-source data architecture and engineering framework that integrates Airflow, Spark, and dbt.

Spark dataframe developers in Brazil - Igor U.
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Igor U.

Vetted Spark dataframe developer in Brazil (UTC-3)

Sr Data Engineer | AWS Solutions Architect Certified | Spark Databricks developer Certified * 📷Sigma Software Group * 📷Federal University of Viçosa I'm Igor and I'm working in the IT area since 2015. I started my career being a software engineer, working on the backend, front end development, and DevOps, but at that time we already handled lots of data, but some datasets had become pretty much larger than we had used to see, so I discovered my real passion: the big data world. So I decided to jump into the data world where I'm until today. I'm a Data Engineer more focused on programming and infrastructure, so I have worked providing larger data engineering teams with some customized tools to help them during their data pipeline development. I have experience in providing and maintaining big data clusters, either on-premises or on the cloud, with some ready-to-use open-source (or customized) tools like Hadoop, Spark, Hive, Presto, Druid, Sqoop, NiFi, and others. Across all my work experience, I have done some user education 1:1s and training sessions to help our consumers on using our tooling efficiently. Also, sometimes I was allocated to some projects in order to help in data pipeline development using both real-time and batch approaches. One of my greatest achievements regarding this was designing and developing an automated framework for ETL development where business users can focus more on data pipeline development rather than what surrounds it. This project has been largely used and improved nowadays by the responsible team. I have also experience with ML in production or MLOps. I have worked as a technical lead in an MLOps squad helping my team on designing and development of a whole ML platform where users can develop, build, deploy and monitor their own ML models using some key concepts like model bias, input/output data drift (data quality and integrity) without any DevOps skills or extra knowledge

Spark dataframe developers in Brazil - Gustavo S.
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Gustavo S.

Vetted Spark dataframe developer in Brazil (UTC-3)

Throughout his career, Gustavo has established himself as a Full Stack Developer and Software Architect, distinguished by his expertise in engineering sophisticated software solutions, steering application development, and leading technology implementations across various sectors. His journey is a testament to his relentless pursuit of excellence in cloud-based applications and data engineering, underscored by his commitment to creating scalable, efficient solutions leveraging first-class and No/Low Code tech stacks. Gustavo's career is characterized by a unique blend of technical prowess and strategic insight, enabling him to simplify complex technical concepts for high-level executives and software engineers alike, thus translating intricate technicalities into strategic business insights. This skill has not only enhanced his ability to deliver impactful presentations but has also solidified his reputation as a trusted "CTO for Hire" within startup accelerators. In this capacity, Gustavo has adeptly coordinated technology strategies, navigated the complexities of managing competing priorities from diverse organizations, and tailored solutions that resonate with client needs with empathy and precision. A defining moment in Gustavo's career was the successful development and implementation of a No/Low Code proof of concept, leading to the execution of a significant project that surpassed scalability and efficiency benchmarks. This achievement highlighted his proficiency in No/Low Code platforms, a skill set he is eager to leverage in guiding enterprise customers to maximize their investments. The cornerstone of Gustavo's work is collaboration, having spent over four years working closely with native teams and managers, honing his understanding of cross-cultural and interdisciplinary team dynamics. His technical repertoire encompasses Python, JavaScript, React, Vue.js, Node.js, alongside expertise in cloud platforms like GCP and AWS, enriched by a solid foundation in data processing frameworks such as PySpark and Apache Kafka. As Gustavo looks towards the future, his ambition is to embrace the role of a Customer Engineer, where he can apply his technical expertise, strategic planning, and organizational skills to cultivate deep relationships with enterprise customers. With more than six years of experience in enterprise-level technical pre-sales and solution consulting, Gustavo is well-equipped to navigate the complexities of customer needs, crafting pathways to technological adoption and transformation that resonate across competitive landscapes.

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Why clients hire Spark dataframe developers with Arc

Without Arc by my side, I would be wasting a lot of time looking for and vetting talent. I'm not having to start a new talent search from scratch. Instead, I’m able to leverage the talent pool that Arc has created.
Mitchum Owen
Mitchum Owen
President of Milo Digital
The process of filling our position took less than a week and they found us a superstar. They've had the flexibility to meet our specific needs every step of the way and their customer service has been top-notch since day one.
Matt Gysel
Matt Gysel
Finance & Strategy at BaseVenture
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.
Philip Tsai
Philip Tsai
Director of Engineering at Chegg

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FAQs

Why hire a Spark dataframe developer?

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 Spark dataframe 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 Spark dataframe developers can help keep your website up-to-date.

How do I hire Spark dataframe developers?

To hire a Spark dataframe 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 Spark dataframe developers effectively and efficiently. Hire full-time Spark dataframe 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 Spark dataframe 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 Spark dataframe 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 Spark dataframe developers for your company, and let Arc handle the logistics.

Where do I hire the best remote Spark dataframe developers?

There are two types of platforms you can hire Spark dataframe 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 Spark dataframe 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 Spark dataframe developers, consider niche platforms like Arc that naturally attract and carefully vet their Spark dataframe developers for hire. This way, you’ll save time and related hiring costs by only interviewing the most suitable remote Spark dataframe developers.

Some factors to consider when you hire Spark dataframe 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 Spark dataframe developers for hire.

How do I write a Spark dataframe developer job description?

Writing a good Spark dataframe developer job description is crucial in helping you hire Spark dataframe 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 Spark dataframe 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 Spark dataframe developers, read our Engineer Job Description Guide & Templates.

What skills should I look for in a Spark dataframe developer?

The top five technical skills Spark dataframe 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 Spark dataframe 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 Spark dataframe developers to keep up with evolving technology and requirements.

What kinds of Spark dataframe developers are available for hire through Arc?

You can find a variety of Spark dataframe developers for hire on Arc! At Arc, you can hire on a freelance, full-time, part-time, or contract-to-hire basis. For freelance Spark dataframe developers, Arc matches you with the right senior developer in roughly 72 hours. As for full-time remote Spark dataframe 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 Spark dataframe developers for hire are all mid-level and senior-level professionals. They are ready to start coding straight away, anytime, anywhere.

Why is Arc the best choice for hiring Spark dataframe developers?

Arc is trusted by hundreds of startups and tech companies around the world, and we’ve matched thousands of skilled Spark dataframe developers with both freelance and full-time jobs. We’ve successfully helped Silicon Valley startups and larger tech companies like Spotify and Automattic hire Spark dataframe developers.

Every Spark dataframe 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 Spark dataframe 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.

How does Arc vet a Spark dataframe developer's skills?

Arc has a rigorous and transparent vetting process for all types of developers. To become a vetted Spark dataframe 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 Spark dataframe 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 Spark dataframe developers, you can rest assured that all remote Spark dataframe developers have been thoroughly vetted for the high-caliber communication and technical skills you need in a successful hire.

How long does it take to find Spark dataframe developers on Arc?

Arc pre-screens all of our remote Spark dataframe developers before we present them to you. As such, all the remote Spark dataframe 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 Spark dataframe developer in 72 hours, or find a full-time Spark dataframe 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 Spark dataframe developers.

How much does a freelance Spark dataframe developer charge per hour?

Depending on the freelance developer job board you use, freelance remote Spark dataframe developers' hourly rates can vary drastically. For instance, if you're looking on general marketplaces like Upwork and Fiverr, you can find Spark dataframe 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 Spark dataframe 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.

How much does it cost to hire a full time Spark dataframe developer?

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 Spark dataframe 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 Spark dataframe developers, check out our FAQs page.

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