How to Become Databricks Certified Apache Spark Developer?

Learn the essential skills with steps to become a certified Apache Spark developer. Kickstart your journey today with career guidance from ProjectPro.

How to Become Databricks Certified Apache Spark Developer?
 |  BY Daivi

With around 35k stars and over 26k forks on Github, Apache Spark is one of the most popular big data frameworks used by 22,760 companies worldwide.


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Apache Spark is the most efficient, scalable, and widely used in-memory data computation tool capable of performing batch-mode, real-time, and analytics operations. The next evolutionary shift in the data processing environment will be brought about by Spark due to its exceptional batch and streaming capabilities. Furthermore, many businesses are now using Databricks, founded by the creators of Apache Spark, as a unified analytics engine for big data and machine learning. The widespread adoption of Apache Spark among organizations worldwide is leading to a rapid increase in the demand for Spark professionals, such as Spark developers. Even though there are many online resources for Spark, achieving certification is a good way to demonstrate your knowledge and stay ahead in the industry. This blog explores the pathway to becoming a successful Databricks Certified Apache Spark Developer and presents an overview of everything you need to know about the role of a Spark developer. 

Apache Spark Developer Jobs - The Demand

Top MNCs like Adobe, Yahoo, Amazon, and many others prefer Spark because of its exceptional performance and reliability. This indicates a significant increase in demand for Spark developers across various domains in the big data industry. Companies seek to hire Spark developers for various tasks, including enhancing programming efficiency, event stream processing, quick, real-time data querying, batch processing of large data sets, etc. Currently, there are over 6000 Spark Developer jobs in the US and over 6000 jobs requiring Spark skills in India.

Who is a Apache Spark Developer ?

Apache Spark Developer is a software developer or a big data developer who specializes in building large data-processing applications or solutions using Apache Spark big data framework. They are also responsible for tuning the performance of Spark applications and troubleshooting any issues that arise during the development and deployment. Apache Spark developers  should have a good understanding of distributed systems and big data technologies. They must also understand how to build a data processing pipeline that can support the five Vs of big data- volume, velocity, variety, veracity, and value- as well as how to transform this data into maintainable code. Python, Java, and Scala knowledge are essential for Apache Spark developers. 

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Apache Spark Developer Skills

You must master the following skills if you want to succeed as an expert-level Spark developer.

  • Various high-level programming languages, including Python, Java, R, and Scala, can be used with Spark, so you must be proficient with at least one or two of them. A spark developer must know one of these programming languages to write efficient and optimized Spark Applications.

  • Knowledge and expertise in Spark components like SparkSQL, SparkMLib, Spark GraphX, SparkR, and Spark Streaming. Knowledge of these Spark API’s is needed to solve real-world business problems and build spark solutions for the same.

  • A good understanding of big data technologies like Hadoop, HDFS, Hive, HBase is important to be able to integrate them with Apache Spark applications .

  • Working knowledge of S3, Cassandra, or DynamoDB.

  • Strong understanding of distributed systems and their key concepts, such as partitioning, replication, consistency, and consensus.

  • Understanding of SQL database integration (Microsoft, Oracle, Postgres, and/or MySQL).

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Apache Spark Developer Roles and Responsibilities

Apache Spark Developer is responsible for building, maintaining, and updating applications using the Spark open-source platform. They work with several Spark ecosystem components, such as Spark SQL, DataFrames, Datasets, and streaming.

Here are some of the key responsibilities of an Apache Spark Developer-

  • Design and Develop efficient and scalable data processing pipelines using Apache Spark.

  • Write and test Apache Spark application code in Scala, Python or Java to implement various data processing tasks.

  • Creating Spark/Scala jobs to aggregate and transform data.

  • Optimize Apache Spark jobs to improve performance and reduce the execution time.

  • Develop and maintain Apache Spark clusters.

  • Generating unit tests for the Spark helper and transformations methods.

  • Developing analytics software, services, and components in Java, Apache Spark, Kafka, Storm, Redis, and other associated technologies like Hadoop and Zookeeper.

  • Running data on distributed SQL, building data pipelines, loading data into databases, using effective machine learning algorithms on a given dataset while ensuring optimum scalability, working with graphs or data streams, etc.

  • Collaborate with cross functional teams to integrate Apache Spark applications and solutions into the overall system architecture.

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Apache Spark Developer Salary 

In the USA, the average yearly compensation for an Apache Spark developer is $144,435. Professionals at the entry-level start at $117,488 a year, while those with the most experience can earn up to $175,000.

In India, an Apache Spark developer has an average yearly income of ₹1,700,000. Professionals at the entry-level begin at ₹1,287,500 a year, while those with the most expertise can earn up to ₹2,915,000 annually.

How to Become a Certified Apache Spark Developer ?

  • Learn the basics of programming languages like Python or Java and important programming concepts like data structures, algorithms, and OOP.

  • Get an in-depth knowledge of various big data concepts like parallel processing, cluster management, distributed computing along with other related topics.

  • Explore the Apache Spark Ecosystem along with other big data technologies like Apache Kafka, Apache Hadoop, and Apache Cassandra as these technologies are often used together with Apache Spark.

  • The key to becoming a successful Apache spark developer is to have hands-on experience working with the Apache Spark Ecosystem.  Start by working on Apache Spark Projects to understand the core concepts of Spark like RDD’s, Dataframes and spark components like Spark MLlib, Spark Streaming, and Spark SQL.

  • Getting a Databricks Apache Spark Certification is a great way to validate your skills and knowledge about the Apache Spark Ecosystem.

What is the Databricks Spark Certification?

The Databricks Apache Spark Developer Associate certification exam tests the candidates' knowledge of the Spark DataFrame API and their ability to use it to carry out simple data manipulation activities within a Spark session. These activities include selecting, renaming, and modifying columns; filtering, deleting, sorting, and combining rows; handling missing data; combining, reading, writing, and splitting DataFrames with schemas; and dealing with UDFs and Spark SQL functions. The exam will also evaluate the fundamentals of the Spark architecture, including execution/deployment modes, the execution hierarchy, fault tolerance, garbage collection, and broadcasting.

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Databricks Apache Spark Developer Certification: Exam Details

The first step for taking the Databricks spark certification exam is to register yourself on the official Databricks certification platform. Also, the exam fee is $200, and a candidate must pay the same amount for every retake. Now, moving on to the essential details about this exam, the total duration of this exam is 120 minutes. The exam comprises 60 multiple-choice questions, and below is a breakdown of the questions-

  • Apache Spark Architecture Concepts – 17% (10/60)

  • Apache Spark Architecture Applications – 11% (7/60)

  • Apache Spark DataFrame API Applications – 72% (43/60)

The exam is available in two programming languages- Python and Scala. So, you must be familiar with either of these languages if you want to earn the Databricks Spark developer certification. It is recommended that you take the practice exam for your preferred language- Python or Scala, before taking the actual exam.

Candidates should enroll in one of the following Databricks Academy courses in order to access the topics tested by the certification exam:

  • The instructor-led Apache Spark Programming with Databricks course.

  • The self-paced Apache Spark Programming with Databricks course.

Furthermore, the course Certification Overview: Databricks Certified Associate Developer for Apache Spark Exam provides candidates with additional information on the certification exam.

Now is the Best Time to Become a Certified Apache Spark Developer!

It’s time to kickstart your journey toward becoming a Databricks Certified Apache Spark Developer. But does earning a certification and acquiring the right skills seem enough to land a job as an Apache Spark developer? Certainly not! You must get your hands dirty working on industry-level Apache Spark projects to get one step ahead of your competitors in the industry. ProjectPro offers over 250 end-to-end solved Big Data and Data Science projects curated by more than 40 industry experts to help you land your dream job in the IT industry.

 

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About the Author

Daivi

Daivi is a highly skilled Technical Content Analyst with over a year of experience at ProjectPro. She is passionate about exploring various technology domains and enjoys staying up-to-date with industry trends and developments. Daivi is known for her excellent research skills and ability to distill

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