Remote Spark developer jobs

We, at Turing, are looking for talented remote Spark developers who will be responsible for cleaning, transforming, and analyzing vast amounts of raw data from various resources using Spark to provide ready-to-use data to the developers and business analysts. Here’s your chance to accelerate your career by working for top Silicon Valley companies.

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Job description

Job responsibilities

  • Create Scala/Spark jobs for data transformation and collection
  • Process huge amounts of unstructured and structured data
  • Write unit tests for data transformation
  • Install, configure and maintain enterprise Hadoop environment
  • Assign schemas using Hive tables and deploy HBase clusters
  • Design data processing pipelines
  • Use ETL tools to load data from different sources into the Hadoop platform
  • Develop and review technical documentation
  • Maintain the security and privacy of Hadoop clusters

Minimum requirements

  • Bachelor’s/Master’s degree in computer science (or equivalent experience)
  • 3+ years of experience working on Spark-based applications (rare exceptions for highly skilled developers)
  • Experience working on complex, large-scale big data environments
  • Hands-on experience in Hive, Yarn, HDFS, HBase, etc.
  • Experience with technologies such as Storm, Apache Kafka, Hadoop, etc.
  • Well-versed in programming languages like Scala, Java, or Python
  • Experience in working in ETL products, like Ab Initio, Informatica, Data Stage, etc.

Preferred skills

  • Expertise in writing complex SQL queries, importing and exporting vast amounts of data using utilities
  • Ability to write abstracted, reusable code components
  • Communicate and coordinate across various teams
  • A good team player with a strong attention to detail

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How to become a Spark developer ?

Due to high speed, ease of use, and complex analytics, Spark has grown tremendously in recent years, becoming the most effective data processing and AI analytical engine in enterprises today. Spark has a high cost because it requires a lot of RAM to run in memory.

Spark combines data and AI by facilitating large-scale data preparation from a variety of sources. It also has a uniform set of APIs for data engineering and data science workloads and seamlessly integrates with popular libraries like TensorFlow, PyTorch, R, and SciKit-Learn.

The popularity of Spark has increased recently as more companies are relying on the data to develop their business strategies. Therefore, Spark development is undeniably a stable and well-paying career option for you.

What is the scope of Spark development?

Big data is the way of the future, and Spark provides a broad set of tools for handling enormous amounts of data in real-time. Spark is a future technology because of its lighting, speed, fault tolerance, and efficient in-memory processing.

Take a look at some pointers that demonstrate why companies prefer Spark.

  • SQL queries, streaming data, machine learning (ML), and graph processing are all supported by this unified engine.
  • For lesser workloads, in-memory processing, disc data storage, and other techniques, it is 100 times quicker than Hadoop.
  • APIs are available for manipulating and transforming semi-structured data that are simple to use.

Web development has advanced to a level that no one could have envisioned 20 years ago. Spark is one of the most popular open-source unified analytics engines these days, and you'll have plenty of career options in the Spark development field.

What are the roles and responsibilities of a Spark developer?

The primary duties of a Spark developer include providing ready-to-use data to feature developers and business analysts by analyzing massive amounts of raw data from diverse systems using Spark. This encompasses both ad-hoc requests and data pipelines incorporated in our production environment.

The main responsibilities of a remote Spark developer jobs include:

  • Write Spark components, analytics, and services executable code.
  • Learn essential programming languages such as Java, Python, and Scala
  • Should know Apache Kafka, Storm, Hadoop, and Zookeeper, as well as other relevant technologies.
  • Be prepared to handle system analysis, which covers design, coding, unit testing, and other SDLC tasks.
  • Take user needs and transform them into strong technical tasks, and provide cost estimates.
  • Validate the accuracy of technical analysis and expertise in problem-solving.
  • Evaluate the code and use-case to confirm that it complies with the specifications.

How to become a Spark developer?

There is a fine line between becoming a certified Spark developer and being an actual Spark developer capable of performing in a real-time application.

Here are some recommendations to help you find remote Spark development jobs.

  • To be an expert, you must follow the right path with expert-level assistance from certified real-time industry professionals in the industry.
  • You can also enroll in any of the training and certification programs.
  • Once the certification process has commenced, you should begin working on your projects to understand Spark better.
  • RDDs (Resilient Distributed Datasets) and Dataframes are Spark's main building components. You need to have an understanding of these.
  • Spark may also be integrated with several high-performance programming languages, including Python, Scala, and Java. PySpark RDDs are the best example of Python and Apache Spark working together.
  • After you've mastered the fundamentals of Spark, you can go on to understand the Major Components of Apache Spark, which are listed below:
    - SparkML-Lib
    - Spark GraphX
    - SparkR
    - Spark Streaming

Once you've completed the necessary training and certification, it's time to create a Spark developer resume and practice what you have learned as much as possible.

Let's take a look at the skills and tactics that a successful Spark developer will require.

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Skills required to become a Spark developer

The first step toward landing remote Spark developer jobs is to learn the core skills. Now, let's have a closer look at it.

1. Big data framing and analysis

Big data analytics uses advanced analytic techniques to extensive, diverse data sets, which can contain structured, semi-structured, and unstructured data and data from many sources and sizes ranging from terabytes to zettabytes. This is an essential skill to get hired for remote Spark developer jobs.

2. Python

Python is an interpreted high-level, general-purpose programming language. Its design philosophy emphasizes code readability by using a lot of indentation. Python’s object-oriented approach is developed to help programmers write clear, logical code for both small and large-scale projects.

3. Scala

Scala is an acronym that stands for Scalable Language. It's a programming language with multiple paradigms. The Scala programming language combines functional and object-oriented programming techniques. It's a statically typed programming language. Its source code is converted to bytecode and run by the Java virtual machine (JVM).

4. Java

Java is an object-oriented programming language with a few implementation dependencies. Java programming language is guaranteed to be a write-once, run-anywhere language. A Java program is compiled into bytecode during compilation. This bytecode format is platform-independent, meaning it may be run on any machine, and it also provides security. Java programs can be run on any machine having Java Runtime Environment installed.

5. Spark SQL

Spark SQL is a structured data processing Spark module. It offers DataFrames as a programming abstraction and may also serve as a distributed SQL query engine. It also has a strong connection to the rest of the Spark ecosystem (e.g., integrating SQL query processing with machine learning). You should develop a grip on the skill to land remote Spark developer jobs.

6. Spark Streaming

Spark Streaming is a Spark API extension that allows data engineers and scientists to analyze real-time data from various sources, including (but not limited to) Kafka, Flume, and Amazon Kinesis. Data can be pushed to file systems, databases, and live dashboards after it has been analyzed.

7. MLlib

MLlib is a scalable machine learning library built on top of Spark that includes classification, regression, clustering, collaborative filtering, dimensionality reduction, and underlying optimization primitives, as well as other standard learning methods and utilities.

8. Elastic MapReduce

Amazon Elastic MapReduce (EMR) is a web service that provides a managed framework for easily, cost-effectively, and securely running data processing frameworks, including Apache Hadoop, Apache Spark, and Presto. It's used for various purposes, including data analysis, online indexing, data warehousing, financial analysis, and scientific simulation. You need to master this to get hired for the best Spark developer jobs.

9. Spark DataFrames and Datasets

Datasets are an extension of data frames in Spark. Essentially, it earns two types of API characteristics: strongly typed and untyped. Unlike data frames, datasets are by default a collection of strongly typed JVM objects. It also makes use of Spark's Catalyst optimizer.

10. GraphX library

GraphX combines ETL, exploratory analysis, and iterative graph computation within just one system. The Pregel API allows you to see the same data as graphs and collections, rapidly transform and combine graphs with RDDs, and implement custom iterative graph algorithms.

Interested in remote Spark developer jobs?

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How to get remote Spark developer jobs?

Spark development is one of the most versatile careers since it allows you to work from any place with an internet connection and a computer. You can work from home or at your favorite workstation if your job allows it! That is precisely what Spark developer jobs can provide.

Working remotely has a lot of advantages. And, the competition has also gone up recently. Therefore, to land successful remote Spark developer jobs, you need to stay on top of your technical skills and establish a productive work routine.

Turing offers the best Spark developer jobs that suit your career trajectories as a Spark developer. Grow your development career by working on challenging technical and business problems using the latest technologies. Join a network of the world's best developers & get full-time, long-term remote Spark developer jobs with better compensation and career growth.

Why become a Spark developer at Turing?

Elite US jobs
Elite US jobs

Long-term opportunities to work for amazing, mission-driven US companies with great compensation.

Career growth
Career growth

Work on challenging technical and business problems using cutting-edge technology to accelerate your career growth.

Exclusive developer community
Exclusive developer community

Join a worldwide community of elite software developers.

Once you join Turing, you’ll never have to apply for another job.
Once you join Turing, you’ll never have to apply for another job.

Turing's commitments are long-term and full-time. As one project draws to a close, our team gets to work identifying the next one for you in a matter of weeks.

Work from the comfort of your home
Work from the comfort of your home

Turing allows you to work according to your convenience. We have flexible working hours and you can work for top US firms from the comfort of your home.

Great compensation
Great compensation

Working with top US corporations, Turing developers make more than the standard market pay in most nations.

How much does Turing pay their Spark developers?

At Turing, every Spark developer is allowed to set their compensation. However, Turing will recommend a salary at which we know we can find a secure and long-term opportunity to grow your Spark developer career. Our recommendations are based on analyzing the prevailing market conditions and the demand from our customers.

Frequently Asked Questions

A Spark developer works on cleaning, transforming, and analyzing huge amounts of raw data from different resources to prepare ready-to-use data for development and analysis purposes. It helps in both ad-hoc requests and also data-pipelines that are embedded in the production environment.

We, at Turing, hire remote developers for over 100 skills like React/Node, Python, Angular, Swift, React Native, Android, Java, Rails, Golang, PHP, Vue, among several others. We also hire engineers based on tech roles and seniority.

Communication is crucial for success while working with American clients. We prefer candidates with a B1 level of English i.e. those who have the necessary fluency to communicate without effort with our clients and native speakers.

Spark developers can work on a wide variety of projects. Using the Spark core data processing engine, you also get access to libraries for SQL, ML, Graph computation and stream processing which can all be used together in applications.

It is the combination of our core business model and values that makes us different from others. We provide full-time, long-term projects to remote developers whereas most of our competitors offer more freelance jobs.

No, the service is absolutely free for software developers who sign up.

We are a Palo Alto-based 'deep' jobs platform allowing talented software developers to work with top US firms from the comfort of their homes. We are led by Stanford alumni and successful A.I. entrepreneurs Jonathan Siddharth and Vijay Krishnan.

After uploading your resume, you will have to go through the three tests -- seniority assessment, tech stack test, and live coding challenge. Once you clear these tests, you are eligible to apply to a wide range of jobs available based on your skills.

No, you don't need to pay any taxes in the U.S. However, you might need to pay taxes according to your country’s tax laws. Also, your bank might charge you a small amount as a transaction fee.

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In a nutshell, Turing aims to make the world flat for opportunity. Turing is the brainchild of serial A.I. entrepreneurs Jonathan and Vijay, whose previous successfully-acquired AI firm was powered by exceptional remote talent. Also part of Turing’s band of innovators are high-profile investors, such as Facebook's first CTO (Adam D'Angelo), executives from Google, Amazon, Twitter, and Foundation Capital.

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