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226 top Big Data Engineering developers available to hire:

Big Data Engineering developers in Canada - Clifford P.
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Clifford P.

Vetted Big Data Engineering developer in Canada (UTC-8)

Results-driven Senior MLOps/DevOps Engineer with extensive experience in designing and scaling cloud infrastructures to support machine learning models. Achieved a 50% reduction in time-to-market through the integration of advanced MLOps practices and automation. Expert in Terraform, SageMaker, TensorFlow, Airflow, Kubeflow, and Kubernetes, driving efficiency across the ML lifecycle, from data ingestion and processing to model deployment. Optimized big data pipelines, improving system efficiency by 40%, while ensuring 99.999% uptime. Proven track record in enhancing deployment reliability by 60% through the implementation of CI/CD pipelines and monitoring systems. Skilled in collaborating with cross- functional teams to deliver impactful, business-driven solutions.

Big Data Engineering developers in Canada - jagdeep M.
jagdeep M.

Big Data Engineering developer in Canada (UTC-3)

A highly motivated, resourceful developer with over 8 years of experience working across multiple platforms, with a wide array of development, build tools, cloud platforms and languages. An analytically minded, creative thinker with experience designing, developing and implementing production applications, databases and other solutions. A very strong communicator with excellent interpersonal skills equally effective working alone or as a member of a team.

Big Data Engineering developers in Canada - Dmitry T.
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Dmitry T.

Vetted Big Data Engineering developer in Canada (UTC-4)

12+ years of development experience. Primary focus is on distributed systems, micro services architecture and cloud native technologies. Strong background in Java and solid understanding of SDLC process. Competent with relational databases and NoSQL storage engines. Quick learner, team player, striving to build long-lasting and robust applications, making use of the best advances in the software engineering domain. **Strong:** Java, Kotlin **Competent**: SQL, JavaScript, Python, Swift **Technologies**: Spring Boot, Hibernate, Jersey, Relational databases (Oracle, MySql), Docker, Kubernetes, OCI (Oracle Cloud), NoSQL (Kafka, Redis, Cassandra)

Big Data Engineering developers in Canada - Ishmeet S.
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Ishmeet S.

Vetted Big Data Engineering developer in Canada (UTC-4)

I am a full-stack engineer and leader with 7+ years of experience building iOS and web apps from scratch using multiple technologies. In addition to working for Microsoft and Royal Bank of Canada (RBC), I co-founded a start-up, developed a suite of cross-platform process automation apps used by manufacturing enterprises across the globe, and generated $500,000+ in less than two years. My industry experience is backed by a master's degree in computer science.

Big Data Engineering developers in Canada - jayant P.
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jayant P.

Vetted Big Data Engineering developer in Canada (UTC-5)

I am a software engineer with 9 years of experience in translating client requirements into end-to-end machine learning systems. Skilled in problem-solving, data modeling, and various technologies including Python, Scala, and Git.

Big Data Engineering developers in Canada - Simon S.
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Simon S.

Vetted Big Data Engineering developer in Canada (UTC-6)

Over the past 7 years, I've accumulated a wide range of professional coding experience—from full-stack web development to AI, machine learning, data science, data engineering, and mobile app development. My deep expertise with the subtleties of Python and TypeScript, combined with my knowledge of recent AI tools, enables me to write efficient code quickly that solves real problems. With an MBA and experience as a startup co-founder, I efficiently blend technical expertise with business objectives. I'm particularly interested in working on data engineering, data science, and AI projects, where I can leverage my skills to drive meaningful impact.

Big Data Engineering developers in Canada - Subhadip M.
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Subhadip M.

Vetted Big Data Engineering developer in Canada (UTC-5)

Specialist in GCP services. Experience in Data Engineering since 2010. Applied Data/machine learning engineer using python for the last few years. Understanding data and applying the ML algorithm to solve use cases include data preparation. Also expertise in making pipeline for data related projects. See more: **https://subhadip.ca**

Big Data Engineering developers in Canada - Patrick H.
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Patrick H.

Vetted Big Data Engineering developer in Canada (UTC-5)

Highly skilled Python Developer with 9+ years of experience in designing and implementing robust software solutions. Proficient in full-stack development, data analysis, and data engineering. Proven track record of delivering high-quality code, collaborating effectively within development teams, and consistently meeting project deadlines. Strong problem-solving abilities and a passion for creating efficient and scalable applications. Well-regarded as a team player with excellent communication skills, fostering collaborative environments and driving successful project outcomes.

Big Data Engineering developers in Canada - Sachi P.
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Sachi P.

Vetted Big Data Engineering developer in Canada (UTC-4)

Over 6+ years of experience in Data Engineering, Data Pipeline Design, Development and Implementation as a Sr. Data Engineer and Data Developer. • Strong experience in Software Development Life Cycle (SDLC) including Requirements Analysis, Design Specification and Testing as per Cycle in both Waterfall and Agile methodologies. • Strong experience in writing scripts using Python API, PySpark API and Spark API for analyzing the data. • Experience with Azure Cloud, Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics, Azure Analytical Service, Big Data Technologies (Apache Spark) • Experience with GCP Cloud Storage, Big Query, Composer, Cloud Dataproc, Cloud SQL, Cloud Functions, Cloud Pub/Sub • Worked on ETL Migration services by creating and deploying AWS Lambda functions to provide a serverless data pipeline that can be written to glue catalog and queried from Athena. • Extensively used Python Libraries PySpark, Pytest, Pymongo, PyExcel, Psycopg, embedPy, NumPy and Beautiful Soup. • Migrated an existing on-premises application to GCP. Used GCP services like Cloud Dataflow and Dataproc for small data sets processing and storage. • Hands On experience on Spark Core, Spark SQL, Spark Streaming and creating the Data Frames handle in SPARK with Scala. • Experience in NoSQL databases and worked on table row key design and to load and retrieve data for real time data processing and performance improvements based on data access patterns. • Experience with Unix/Linux systems with scripting experience and building data pipelines. • Extensive experience in Hadoop Architecture and various components such as HDFS, Job Tracker, Task Tracker, Name Node, Data Node, and Map Reduce concepts. • Performed complex data analysis and provided critical reports to support various departments. • Expertise in development of various reports, dashboards using various PowerBI and Tableau Visualizations • Experience in building large scale highly available Web Applications. Working knowledge of web services and other integration patterns. • Experienced with version control systems like Git, GitHub, CVS, and SVN to keep the versions and configurations of the code organized. Efficiently facilitating task tracking and issue management using JIRA. • Good communication skills, work ethics and the ability to work in a team efficiently with good leadership skills. • Experience with continuous integration and automation using Jenkins. • Experience building docker image using accelerator and scanning images using various scanning techniques • Over 6+ years of experience in Data Engineering, Data Pipeline Design, Development and Implementation as a Sr. Data Engineer and Data Developer. • Strong experience in Software Development Life Cycle (SDLC) including Requirements Analysis, Design Specification and Testing as per Cycle in both Waterfall and Agile methodologies. • Strong experience in writing scripts using Python API, PySpark API and Spark API for analyzing the data. • Experience with Azure Cloud, Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics, Azure Analytical Service, Big Data Technologies (Apache Spark) • Experience with GCP Cloud Storage, Big Query, Composer, Cloud Dataproc, Cloud SQL, Cloud Functions, Cloud Pub/Sub • Worked on ETL Migration services by creating and deploying AWS Lambda functions to provide a serverless data pipeline that can be written to glue catalog and queried from Athena. • Extensively used Python Libraries PySpark, Pytest, Pymongo, PyExcel, Psycopg, embedPy, NumPy and Beautiful Soup. • Migrated an existing on-premises application to GCP. Used GCP services like Cloud Dataflow and Dataproc for small data sets processing and storage. • Hands On experience on Spark Core, Spark SQL, Spark Streaming and creating the Data Frames handle in SPARK with Scala. • Experience in NoSQL databases and worked on table row key design and to load and retrieve data for real time data processing and performance improvements based on data access patterns. • Experience with Unix/Linux systems with scripting experience and building data pipelines. • Extensive experience in Hadoop Architecture and various components such as HDFS, Job Tracker, Task Tracker, Name Node, Data Node, and Map Reduce concepts. • Performed complex data analysis and provided critical reports to support various departments. • Expertise in development of various reports, dashboards using various PowerBI and Tableau Visualizations • Experience in building large scale highly available Web Applications. Working knowledge of web services and other integration patterns. • Experienced with version control systems like Git, GitHub, CVS, and SVN to keep the versions and configurations of the code organized. Efficiently facilitating task tracking and issue management using JIRA. • Good communication skills, work ethics and the ability to work in a team efficiently with good leadership skills. • Experience with continuous integration and automation using Jenkins. • Experience building docker image using accelerator and scanning images using various scanning techniques

Big Data Engineering developers in Canada - Rohith S.
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Rohith S.

Vetted Big Data Engineering developer in Canada (UTC-7)

7 years of experience in Data Engineering Python/Scala Spark Developer | Azure | Big data TECHNICAL SKILLS Languages, APIs: Python, Scala, Spark, SQL Platforms: MapR Azure: Azure Data Factory, Azure Data lake storage, Databricks, Synapse Analytics IDEs/Software: Jupyter/Zeppelin Notebooks, IntelliJ, Hue, Jira, Fisheye Databases: Oracle, IBM DB2, MapRDB (NoSQL) Visualization Tools: Tableau CI/CD: Jenkins, Linux commands, Shell scripting, Control-M Version Control: GIT Visa: Permanent Resident Canada

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Why clients hire Big Data Engineering 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 Big Data Engineering 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 Big Data Engineering 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 Big Data Engineering developers can help keep your website up-to-date.

How do I hire Big Data Engineering developers?

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

Where do I hire the best remote Big Data Engineering developers?

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

Some factors to consider when you hire Big Data Engineering 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 Big Data Engineering developers for hire.

How do I write a Big Data Engineering developer job description?

Writing a good Big Data Engineering developer job description is crucial in helping you hire Big Data Engineering 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 Big Data Engineering 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 Big Data Engineering developers, read our Software Engineer Job Description Guide & Templates.

What skills should I look for in a Big Data Engineering developer?

The top five technical skills Big Data Engineering 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 Big Data Engineering 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 Big Data Engineering developers to keep up with evolving technology and requirements.

What kinds of Big Data Engineering developers are available for hire through Arc?

You can find a variety of Big Data Engineering developers for hire on Arc! At Arc, you can hire on a freelance, full-time, part-time, or contract-to-hire basis. For freelance Big Data Engineering developers, Arc matches you with the right senior developer in roughly 72 hours. As for full-time remote Big Data Engineering 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 Big Data Engineering 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 Big Data Engineering developers?

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

Every Big Data Engineering 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 Big Data Engineering 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 Big Data Engineering developer's skills?

Arc has a rigorous and transparent vetting process for all types of developers. To become a vetted Big Data Engineering 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 Big Data Engineering 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 Big Data Engineering developers, you can rest assured that all remote Big Data Engineering 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 Big Data Engineering developers on Arc?

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

How much does a freelance Big Data Engineering developer charge per hour?

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

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 Big Data Engineering 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 Big Data Engineering developers, check out our FAQs page.

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