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5,780 Remote Big Data Engineering developers and experts available to hire:

Biswajit G., Big Data Engineering developer
Biswajit G.

Big Data Engineering developer in the United States (UTC-4)

I like to work around multiple technologies. Currently playing with AWS, Big Data, Hadoop where in my main goal is to achieve Big-Data Solutions using Hadoop, Spark and related BigData Technologies. I enjoy collecting and integrating billions of data records to provide 360 degree view of data and I have great passion for Data Warehousing and Big Data Analytics. • Experienced in designing and developing "Big" DWH using Hadoop ecosystem. • Experience in Cloud AWS and GCP. Good understanding of MapReduce programming model. • Extensively used Spark-SQL & Hive Query Language (HQL) for getting customer insights which will be used for critical decision making by business users. • Strong experience with the Python / Scala programming language. • Knowledge of Shell scripting. • Experience with one or more Hadoop distributions, e.g. Hortonworks, Cloudera. • Experience in handling and processing huge amount of data using Hadoop. Specialties : AS, GCP, Python, Snowflake, Redis, Elastic Cache, Jenkins, Kuberetes, Terraform, Apache Airflow,Docker,Hadoop, Hive,Pig, Map Reduce, Sqoop, Apache Storm, Apache Spark, Spark Streaming, Oozie, Sql, Pl/Sql, Unix, Data Analysis, Data Warehousing, ETL Development,Data visualizations using BIRT and Tableau.

Data Engineering • 5 yrsAzure Data Factory • 2 yrsAzureAIGoogle Cloud PlatformPythonJenkinsApache SparkMicroservicesSolution ArchitectureFinancial AnalysisAWS LambdaInfrastructure as CodeAws cliSnowflakeAws iamAws elastic beanstalkDatabricksDevOpsAWSAWS Cloud Infrastructure
+14
Apache Spark, Microservices, Solution Architecture, Financial Analysis, AWS Lambda, Infrastructure as Code, Aws cli, Snowflake, Aws iam, Aws elastic beanstalk, Databricks, DevOps, AWS, AWS Cloud Infrastructure
Clifford P., Big Data Engineering developer
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Clifford P.

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

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 DataSite Reliability EngineeringPythonDevOpsTerraformGitCI/CDMachine learningMLOpsAzureJenkinsAnsiblePython 3PipelinesApache SparkKubernetesTensorFlowAirflowMLflowAWSScalabilityCloud SecurityHigh reliability organizationGoogle Cloud PlatformApache Kafka
+18
Machine learning, MLOps, Azure, Jenkins, Ansible, Python 3, Pipelines, Apache Spark, Kubernetes, TensorFlow, Airflow, MLflow, AWS, Scalability, Cloud Security, High reliability organization, Google Cloud Platform, Apache Kafka
Divine-Hope E., Big Data Engineering developer
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Divine-Hope E.

Vetted Big Data Engineering developer in Portugal

As a Data Engineer with expertise in Python, SQL, Streaming, Data Modelling, and big data technologies, I specialize in building scalable and real-time data pipelines and data products, transforming complex data into clear, actionable insights. My proficiency extends to deploying machine learning models and creating RAG pipelines to leverage LLM capabilities, empowering businesses with data-driven decision-making tools to foster growth and efficiency.

Data Engineering • 7 yrsData warehouse • 6 yrsBig DataAzure Data FactoryGoogle Cloud PlatformPythonSQLApache KafkaAWSSnowflakeAPIPostgreSQLGoogle BigQueryTerraformApache AirflowDBTMongoDBMixpanelAirflowMetabaseDebeziumTableauApache SparkMicrosoft SQL ServerDatabricks
+18
Apache Kafka, AWS, Snowflake, API, PostgreSQL, Google BigQuery, Terraform, Apache Airflow, DBT, MongoDB, Mixpanel, Airflow, Metabase, Debezium, Tableau, Apache Spark, Microsoft SQL Server, Databricks
Chinmay M., Big Data Engineering developer
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Chinmay M.

Vetted Big Data Engineering developer in India (UTC+6)

Application Developer in a wide variety of business applications. Particularly interested in server side technologies. Experienced in Java J2EE web application development including Content Management System (Alfresco), Portal Applications (Liferay and SharePoint). Experience in interfacing different business application using middleware servers (BizTalk, SSIS). Experience in Big Data Implementation using Spark, Scala, Hive, Hbase, and Pig. Experience in various domain like banking (credit card application), media & entertainment, Logistic and manufacturing. Specialties: Big Data Application implementation in Scala and spark using Horton works platform. Design and Implemented projects with data load up to 1 TB per hour with complex transformation.

Data Engineering • 8 yrsBig DataSQLApache KafkaPythonApache HadoopApache AirflowApache SparkMicroservicesGrafanaKubernetesDockerScalaPython 3JavaDatabase
+9
Apache Spark, Microservices, Grafana, Kubernetes, Docker, Scala, Python 3, Java, Database
Brian P., Big Data Engineering developer
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Brian P.

Vetted Big Data Engineering developer in Italy (UTC+1)

14+ years of experience across backend systems, databases, and application development. Passionate about clean interfaces, good documentation, and open-source. Extensively experienced with: Go, Rust, Javascript-HTML-CSS, Nix, Bash, Lua; Redis, Postgres, MySQL/MariaDB, Cassandra/Scylla, Mongo; Caddy, Prometheus/Grafana, ELK stack; Kubernetes, Docker/Podman, Gitlab CI; Many flavors of Linux. EU-based, with 9+ years of experience working remotely as a developer. Well-versed in communicating over Slack, Zoom, and email, and in maintaining good working relationships across large time zone differences. I also have past experience with many other languages and tools that I could easily pick back up.

Big DataGoRedisRustSQLBashGitLab CI/CDHTML/CSSJavaScriptKubernetesPythonDockerRESTful APIDevOpsCassandraJiraJwtMicroservicesSystem securityAWSMongoDBGoogle Cloud PlatformJSON-RPCetcd
+17
HTML/CSS, JavaScript, Kubernetes, Python, Docker, RESTful API, DevOps, Cassandra, Jira, Jwt, Microservices, System security, AWS, MongoDB, Google Cloud Platform, JSON-RPC, etcd
Aissam C., Big Data Engineering developer
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Aissam C.

Vetted Big Data Engineering developer in France (UTC+1)

I am a skilled Lead Data Engineer with expertise in Big Data, Data Pipelines, Backend Development, and various tools like Spark, SQL, AWS, and Snowflake. My experience includes optimizing pipelines, implementing data models, and achieving significant cost savings.

Data Engineering • 5 yrsBig DataData modelingAWSSQLApache SparkPythonPerformance OptimizationGitLabSnowflakeDBTSkySpark
+5
Performance Optimization, GitLab, Snowflake, DBT, SkySpark
Uriel Z., Big Data Engineering developer
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Uriel Z.

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

I am a software specialist with more than 17 years of experience in the development and innovation of business applications, business processes and integration components for banking, telecommunications and insurance. With responsibilities like leading, designing, developing and releasing to production high quality products.

Big DataHTML/CSSJavaScriptAPIShopifyMagentoRubyPythonJavaGitAmazon S3SalesforceServiceNowCloudWatchSplunkTerraformAWS LambdaCamundaAppianBPMNAWSCeligo integrationWebSphereReactIBMIBM ODMJenkinsCloudIntegrationContainersOpenShiftContinuous DeploymentMicroservicesAppian BPMCloud AutomationDevOps
+29
Python, Java, Git, Amazon S3, Salesforce, ServiceNow, CloudWatch, Splunk, Terraform, AWS Lambda, Camunda, Appian, BPMN, AWS, Celigo integration, WebSphere, React, IBM, IBM ODM, Jenkins, Cloud, Integration, Containers, OpenShift, Continuous Deployment, Microservices, Appian BPM, Cloud Automation, DevOps
Joshua P., Big Data Engineering developer
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Joshua P.

Vetted Big Data Engineering developer in New Zealand (UTC+13)

From a computational physicist with 30+ publications, I've transitioned into lead roles within software and data development. Being an expert in multiple coding languages, cloud platforms, and frameworks, I mentor (and learn from) junior colleagues to strengthen our team culture. I am seeking senior technical leadership roles that combine strategic planning and team management with hands-on technical contributions.

Startup experienceData Engineering • 10 yrsData modeling • 10 yrsData warehouse • 6 yrsData analytics strategy • 5 yrsData analysisExploratory Data AnalysisBig Data EngineeringPythonPhysics SimulationMathematical ProgrammingLeadershipSQLNode.jsTailwind cssDBTAWSPandasAWS CDKC++Unreal Engine
+13
Python, Physics Simulation, Mathematical Programming, Leadership, SQL, Node.js, Tailwind css, DBT, AWS, Pandas, AWS CDK, C++, Unreal Engine
Rafael F., Big Data Engineering developer
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Rafael F.

Vetted Big Data Engineering developer in Brazil (UTC-3)

Seasoned professional with over 5 years of experience delivering cloud-based data solutions. Currently serving as a Senior Data Engineer and System Integration Lead, I excel in orchestrating complex data migrations and designing efficient data models and pipelines to drive business success. Proven track record of working remotely with international teams, leveraging asynchronous communication to effectively collaborate and manage projects across time zones. Skilled in communication, planning, documentation, and liaising between stakeholders to ensure seamless project execution.

Data architecture • 6 yrsData warehouse • 5 yrsData Engineering • 5 yrsData modeling • 5 yrsBig DataSQLPythonETLPower BIBigQuery MLWeb ScrapingSalesforceVirtualizationGit flowContinuous DeploymentApache AirflowMachine learningHeuristicsDeep LearningRESTful APIOpen Source SoftwareTime Series Analysis
+15
ETL, Power BI, BigQuery ML, Web Scraping, Salesforce, Virtualization, Git flow, Continuous Deployment, Apache Airflow, Machine learning, Heuristics, Deep Learning, RESTful API, Open Source Software, Time Series Analysis
Bruno O., Big Data Engineering developer
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Bruno O.

Vetted Big Data Engineering developer in Brazil (UTC-3)

I’m a passionate Software & Data Engineer with 15 years of experience designing and developing high-throughput, event-driven Microservices and batch and stream processing data pipelines that handle several terabytes daily. I thrive best on fast-paced environments where teams have the autonomy to innovate and experiment with new ideas.

Data Engineering • 7 yrsApache KafkaJavaPythonAWSApache SparkAirflowKotlinScalaDBTKubernetesGoNew RelicPostgreSQLDatabase SchemaDatadogRedisElasticsearchGoogle BigQueryDataflowSkySpark
+14
Kotlin, Scala, DBT, Kubernetes, Go, New Relic, PostgreSQL, Database Schema, Datadog, Redis, Elasticsearch, Google BigQuery, Dataflow, SkySpark

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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 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 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 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 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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