Project Manager at computer examining code and working on project

Many years ago, Apache Hadoop enjoyed a lot of hype. Companies around the world relied upon it to crunch huge, distributed datasets for crucial strategic insights. While that hype has faded, and cloud-based data platforms can replicate much of Hadoop’s functionality, Hadoop is still utilized by thousands of organizations around the world. As a result, there’s still demand for Hadoop developers—provided they can serve up an excellent Hadoop developer resume.

Let’s dig into the necessary components of a Hadoop developer resume, along with some tips on how to improve yours. We’ll end with a sample Hadoop developer resume that you can use as a template when writing your own.

What is Apache Hadoop?

In simplest terms, Apache Hadoop is an open-source framework that allows organizations to run data applications on large hardware clusters. Soon after its release in 2006, large companies began to leverage Hadoop to run massive “clusters”; by 2013, thousands of companies relied on the software for distributed storage and compute of large amounts of data. Companies such as IBM, Hortonworks, Pivotal and Cloudera rolled out their own specialized Hadoop distributions.

Apache Hadoop includes the Hadoop Distributed File System (HDFS) and MapReduce (for processing), along with YARN and Hadoop Common (which features the libraries that the ecosystem needs to operate). It guides data in various hardware nodes to process in parallel, speeding up compute. For years, knowing Hadoop was essential for a variety of tech jobs, from back-end developers and data analysts to DevOps and Python engineers.

What do I need to know to land an Apache Hadoop job?

In order to survive an interview for an Apache Hadoop developer position, you should understand the technology’s fundamentals, as well as the challenges facing anyone attempting to run a Hadoop distribution. A hiring manager or recruiter will ask you about everything from building scalable distributed data solutions to importing and exporting data to your knowledge of business requirements.

With Apache Hadoop developer job postings, the following skills are frequently mentioned:

If you’re heading into an interview for a Hadoop developer position, you should take the time to ask your interviewer about the company’s current data architecture. That will give you crucial insight into what you’ll need to do, including the modification of any existing Hadoop setup.

What do I need to include in an Apache Hadoop developer resume?

Before composing your Apache Hadoop developer resume, consult the original job posting. Which skills does it mention? Which of those skills have you mastered? Make sure those skills are mentioned in your own resume, because many companies rely on automated resume scanning software that will search for those terms (and potentially delete your resume if they’re not included).

For example, if the job posting mentions MapReduce, Hive, and Java, make sure you list them in your resume (provided you know them, of course; never list a skill you don’t actually know). Beyond that, you’ll want to illustrate how you used your Hadoop skills to help your previous employers succeed at their data-analysis efforts.

What does a sample Apache Hadoop resume look like?

You should always tailor an Apache Hadoop developer resume to a specific job. Use this template as a foundation as you customize your skills and experience to match a potential employer’s needs and goals:

 

Anna Burke123 Any St. Apt. 102 LinkedIn ▪ GitHub ▪ Google+ East Brunswick, NJ 00000 000. 555.1212aburke@email.com

Profile: Hadoop Stack Developer and Administrator

“Transforming large, unruly data sets into competitive advantages”

Purveyor of competitive intelligence and holistic, timely analyses of Big Data made possible by the successful installation, configuration and administration of Hadoop ecosystem components and architecture.

  • Two years’ experience installing, configuring, testing Hadoop ecosystem components.
  • Capable of processing large sets of structured, semi-structured and unstructured data and supporting systems application architecture.
  • Able to assess business rules, collaborate with stakeholders and perform source-to-target data mapping, design and review.
  • Familiar with data architecture including data ingestion pipeline design, Hadoop information architecture, data modeling and data mining, machine learning and advanced data processing. Experience optimizing ETL workflows.
  • Hortonworks Certified Hadoop Developer, Cloudera Certified Hadoop Developer and Certified Hadoop Administrator.

Areas of Expertise:

  • Big Data Ecosystems: Hadoop, MapReduce, HDFS, HBase, Zookeeper, Hive, Pig, Sqoop, Cassandra, Oozie, Flume, Chukwa, Pentaho Kettle and Talend
  • Programming Languages: Java, C/C++, eVB, Assembly Language (8085/8086)
  • Scripting Languages: JSP & Servlets, PHP, JavaScript, XML, HTML, Python and Bash
  • Databases: NoSQL, Oracle
  • UNIX Tools: Apache, Yum, RPM
  • Tools: Eclipse, JDeveloper, JProbe, CVS, Ant, MS Visual Studio
  • Platforms: Windows(2000/XP), Linux, Solaris, AIX, HPUX
  • Application Servers: Apache Tomcat 5.x 6.0, Jboss 4.0
  • Testing Tools: NetBeans, Eclipse, WSAD, RAD
  • Methodologies: Agile, UML, Design Patterns

Professional Experience: Hadoop Developer Investor Online Network, Englewood Cliff, New Jersey 2019 to present Facilitated insightful daily analyses of 60 to 80GB of website data collected by external sources. Spawning recommendations and tips that increased traffic 38% and advertising revenue 16% for this online provider of financial market intelligence.

  • Developed MapReduce programs to parse the raw data, populate staging tables and store the refined data in partitioned tables in the EDW.
  • Created Hive queries that helped market analysts spot emerging trends by comparing fresh data with EDW reference tables and historical metrics.
  • Enabled speedy reviews and first mover advantages by using Oozie to automate data loading into the Hadoop Distributed File System and PIG to pre-process the data.
  • Provided design recommendations and thought leadership to sponsors/stakeholders that improved review processes and resolved technical problems.
  • Managed and reviewed Hadoop log files.
  • Tested raw data and executed performance scripts.
  • Shared responsibility for administration of Hadoop, Hive and Pig.

Hadoop Developer/Administrator Bank of the East, Yonkers, New York2012 to 2013 Helped this regional bank streamline business processes by developing, installing and configuring Hadoop ecosystem components that moved data from individual servers to HDFS.

  • Installed and configured MapReduce, HIVE and the HDFS; implemented CDH3 Hadoop cluster on CentOS. Assisted with performance tuning and monitoring.
  • Created HBase tables to load large sets of structured, semi-structured and unstructured data coming from UNIX, NoSQL and a variety of portfolios.
  • Supported code/design analysis, strategy development and project planning.
  • Created reports for the BI team using Sqoop to export data into HDFS and Hive.
  • Developed multiple MapReduce jobs in Java for data cleaning and preprocessing.
  • Assisted with data capacity planning and node forecasting.
  • Collaborated with the infrastructure, network, database, application and BI teams to ensure data quality and availability.
  • Administrator for Pig, Hive and Hbase installing updates, patches and upgrades.

Java Developer New York Bank, New York, New York2010 to 2012 Improved user satisfaction and adoption rates by designing, coding, debugging, documenting, maintaining and modifying a number of apps and programs for ATM and online banking. Participated in Hadoop training and development as part of a cross-training program.

  • Led the migration of monthly statements from UNIX platform to MVC Web-based Windows application using Java, JSP, Struts technology.
  • Prepared use cases, designed and developed object models and class diagrams.
  • Developed SQL statements to improve back-end communications.
  • Incorporated custom logging mechanism for tracing errors, resolving all issues and bugs before deploying the application in the WebSphere Server.
  • Received praise from users, shareholders and analysts for developing a highly interactive and intuitive UI using JSP, AJAX, JSF and JQuery techniques.
  • View samples at www.myportfolio.com/aburke

Education, Training and Professional Development New Jersey Institute of Technology, BS Computer Science Hadoop Training Accelebrate: “Hadoop Administration Training” Cloudera University Courses: “Hadoop Essentials” and “Hadoop Fundamentals I & II” MapReduce Courses: “Introduction to Apache MapReduce and HDFS,” “Writing MapReduce Applications” and “Intro to Cluster Administration” Nitesh Jain: “Become a Certified Hadoop Developer” Member, Hadoop Users Group of New Jersey