Hire the Top 2% of
Remote Spark dataframe Developers

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 developers, 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.

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 engineers 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 developer for your company, and let Arc handle the logistics.

There are two types of platforms you can hire Spark dataframe programmers 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 developer candidates.

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.

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

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 software 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.

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 programmers, 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 software 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.

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 (both for depth in Spark dataframe and breadth across the greater domain). 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 engineer 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 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.

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 programmer in 72 hours, or find a full-time Spark dataframe programmer 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.

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.

According to the U.S. Bureau of Labor Statistics, the medium annual wage for software 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.