Hadoop Platform Engineer Job Description [Updated for 2025]

In this era of big data, the need for Hadoop Platform Engineers is more critical than ever.

As our data-driven world expands, the demand for skilled professionals who can organize, manage, and protect our vast data repositories grows exponentially.

But what does being a Hadoop Platform Engineer really entail?

Whether you are:

• A job seeker looking to understand the core of this role,
• A hiring manager drafting the perfect candidate profile,
• Or simply fascinated by the intricacies of big data engineering,

You’ve come to the right place.

Today, we present a tailor-made Hadoop Platform Engineer job description template, perfect for easy posting on job boards or career sites.

Let’s dive right in.

Hadoop Platform Engineer Duties and Responsibilities

Hadoop Platform Engineers are responsible for the design, development, and maintenance of Hadoop platforms to analyze large sets of data.

They also collaborate with data scientists and architects on several projects.

Their duties and responsibilities include:

• Designing and deploying Hadoop platforms and services with a focus on high availability, fault tolerance, and scalability
• Configuring and maintaining Hadoop clusters and its ecosystems
• Performing big data processing using Hadoop, MapReduce, Sqoop, Oozie, and Impala
• Implementing complex Hadoop-based applications and supporting a high frequency of data loads and extracts
• Developing data pipeline using Hadoop components like HDFS, Spark, and HBase
• Monitoring Hadoop cluster job performances and capacity planning
• Troubleshooting and debugging any Hadoop ecosystem run-time issues
• Securing Hadoop cluster using Kerberos or other security tools
• Working closely with data architects, data scientists, and other stakeholders to ensure development and implementation of new data solutions
• Creating and maintaining documentation on Hadoop platform services

 

Hadoop Platform Engineer Job Description Template

Job Brief

We are seeking a knowledgeable and experienced Hadoop Platform Engineer to join our team.

The successful candidate will be responsible for the design, development, installation, and support of our Hadoop environment.

The Hadoop Platform Engineer will help define architectural standards and frameworks, and ensure our Hadoop services are robust and reliable.

The ideal candidate has a strong background in software development and experience with Hadoop ecosystem, including HDFS, MapReduce, Hive, and HBase.

 

Responsibilities

• Design and implement Hadoop infrastructure for scalable and reliable data storage and processing.
• Implement security, encryption, and access control for Hadoop clusters.
• Perform capacity planning and performance tuning for Hadoop clusters.
• Work closely with data scientists and analysts to optimize data processing.
• Resolve complex technical issues related to Hadoop.
• Stay updated with the latest Hadoop technologies and apply them where applicable.
• Document system configurations, operational procedures, and architectural diagrams.
• Collaborate with software engineers to integrate Hadoop with existing applications.
• Participate in system maintenance and upgrades.
• Comply with project plans and industry standards.

 

Qualifications

• Proven work experience as a Hadoop Platform Engineer or similar role in Big Data.
• Deep understanding of Hadoop architecture and core Hadoop ecosystem components.
• Experience with Hadoop cluster setup, configuration, and management.
• Knowledge of scripting languages such as Python or Bash.
• Experience with cloud services like AWS or Azure is a plus.
• Knowledge of SQL, NoSQL databases, and ETL tools.
• Strong problem-solving and troubleshooting skills.
• BSc degree in Computer Science, Engineering or relevant field.

 

Benefits

• 401(k)
• Health insurance
• Dental insurance
• Retirement plan
• Paid time off
• Professional development opportunities

 

Additional Information

• Job Title: Hadoop Platform Engineer
• Work Environment: Office setting with options for remote work. Some travel may be required for team meetings or client consultations.
• Reporting Structure: Reports to the Lead Data Engineer or Data Engineering Manager.
• Salary: Salary is based upon candidate experience and qualifications, as well as market and business considerations.
• Pay Range: $120,000 minimum to $180,000 maximum
• Location: [City, State] (specify the location or indicate if remote)
• Employment Type: Full-time
• Equal Opportunity Statement: We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
• Application Instructions: Please submit your resume and a cover letter outlining your qualifications and experience to [email address or application portal].

 

What Does a Hadoop Platform Engineer Do?

Hadoop Platform Engineers typically work for large corporations, IT firms, or data-focused companies.

They can also work as freelancers or consultants on a contractual basis.

They work closely with other data professionals like Data Architects, Data Analysts, and Data Scientists to design, install, and maintain highly scalable and robust Hadoop environments.

They are experts in handling data platform issues related to performance, security, and data integration.

Their job is to create, modify, and test Hadoop applications.

They use Hadoop scripting languages to write MapReduce or Spark jobs, perform ETL tasks, and data summary jobs.

They also work on data ingestion processes using tools like Sqoop and Flume, and data processing using Hive, Pig, or custom MapReduce jobs.

They are responsible for ensuring optimal performance of Hadoop clusters and the big data platforms.

They manage jobs, queue, and HDFS capacity to ensure high availability and performance.

A Hadoop Platform Engineer often works on troubleshooting complex issues that arise in the Hadoop environment and also implements necessary security measures to protect the data.

They constantly monitor the Hadoop cluster and platform, implement automated processes for data extraction, and perform data cleaning and data quality checks.

They also liaise with other teams to ensure smooth operations and effective collaboration in data-related projects.

Hadoop Platform Engineers are also responsible for updating the system as per new business requirements or technological advancements, keeping the Hadoop environment up to date and efficient.

They are consistently working towards improving the system, resolving technical problems, and enhancing data processing capabilities.

 

Hadoop Platform Engineer Qualifications and Skills

A competent Hadoop Platform Engineer should possess a combination of technical expertise, problem-solving abilities, and collaborative skills, including:

• Deep understanding of the Hadoop ecosystem and its components like HDFS, YARN, MapReduce, Hive, Pig, HBase, and others.
• Proficiency in writing complex MapReduce programs and the ability to work with both structured and unstructured data.
• Exceptional programming skills in languages like Java, Python, Scala, or R for the development and maintenance of Hadoop applications.
• Ability to design and implement end-to-end solutions using ETL tools, specifically for Hadoop environments.
• Good understanding of data loading tools like Flume and Sqoop, and experience with workflow/schedulers like Oozie.
• Problem-solving skills to debug and solve complex Hadoop cluster issues, optimize for performance and ensure high availability.
• Strong communication skills to effectively collaborate with data scientists, business analysts, and other team members to understand requirements and translate them into technical solutions.
• Experience in SQL, database systems, and data warehousing solutions for data integration tasks and data analysis.
• Knowledge of Linux operating system and the ability to write shell scripts for automation.
• Understanding of cloud platforms like AWS, Azure, or Google Cloud and experience with containerization technologies such as Docker and Kubernetes can be beneficial.

 

Hadoop Platform Engineer Experience Requirements

Hadoop Platform Engineers often start with a bachelor’s degree in computer science, information technology, or a related field, which usually involves practical experience in data management and software development.

The entry-level position typically requires 1 to 2 years of experience, generally gained through an internship, part-time, or full-time roles dealing with Hadoop platform and other Big Data technologies.

Candidates can also gain on-the-job experience in roles such as Data Analyst, Systems Engineer, or other IT-related roles.

Candidates with more than 3 years of experience often have in-depth knowledge of Hadoop Ecosystem and its components like HDFS, MapReduce, Hive, Pig, HBase etc.

They also may have practical experience in managing and analyzing large datasets, and have developed advanced programming skills, especially in Java, Python, and SQL.

Those with more than 5 years of experience are likely to have some leadership experience in their background.

They may have developed an expertise in designing, installing, configuring, and maintaining Hadoop clusters, and often have experience with related technologies like NoSQL databases, data warehousing solutions, and cloud platforms.

They are typically ready for a senior, lead, or managerial position in the Hadoop platform engineering team.

Furthermore, Hadoop Platform Engineers who possess certifications such as the Cloudera Certified Hadoop Developer (CCHD) or Hortonworks Certified Apache Hadoop Developer (HCAHD) are often preferred as these certifications demonstrate a thorough understanding of Hadoop principles and its application.

 

Hadoop Platform Engineer Education and Training Requirements

Hadoop Platform Engineers typically hold a bachelor’s degree in computer science, information technology, data science, or a related field.

Strong knowledge of Hadoop and its associated programming languages such as Java, Python, or Scala is necessary.

Understanding of Hadoop ecosystem components like HDFS, MapReduce, HBase, Hive, Yarn, Pig, and Oozie are essential for this role.

Experience with NoSQL databases, such as HBase, Cassandra, or MongoDB, and SQL databases is also required.

Some positions may require a master’s degree in a specialized IT or data science discipline.

In addition to academic qualifications, Hadoop Platform Engineers should have hands-on experience in managing, troubleshooting and debugging Hadoop clusters.

Professional certifications like Cloudera Certified Hadoop Developer (CCHD) or Hortonworks Certified Apache Hadoop Developer (HCAHD) are often preferred as they demonstrate the candidate’s skills and commitment to the field.

Continuous learning and staying updated with the latest Hadoop versions and enhancements is important for career advancement.

 

Hadoop Platform Engineer Salary Expectations

A Hadoop Platform Engineer earns an average salary of $120,000 (USD) per year.

However, the actual earnings can differ based on factors such as experience, certifications in Hadoop or related technologies, the complexity of the project or tasks, geographical location, and the employing organization.

 

Hadoop Platform Engineer Job Description FAQs

What skills does a Hadoop Platform Engineer need?

A Hadoop Platform Engineer needs strong technical skills in Hadoop ecosystem and various related technologies like MapReduce, HDFS, HBase, Zookeeper, Pig, Hive, Sqoop, etc.

They should have good knowledge of programming languages like Java, Scala, and Python.

Additionally, proficiency in SQL, data modeling, and data processing is required.

They also need to have problem-solving skills, a good understanding of algorithms and data structures, and the ability to work with large data sets.

 

Do Hadoop Platform Engineers need a degree?

While not always a strict requirement, most employers prefer Hadoop Platform Engineers to have a Bachelor’s degree in Computer Science, Information Systems, or a related field.

Some might even prefer a Master’s degree or relevant certifications.

It’s also important to have hands-on experience with Hadoop and other big data technologies, which can be acquired through internships, part-time jobs, or even personal projects.

 

What should you look for in a Hadoop Platform Engineer resume?

Look for a strong foundation in Computer Science including data structures, algorithms, and software design.

Knowledge and experience in Hadoop and its related technologies should be highlighted.

Certifications like Cloudera Certified Hadoop Developer or Hortonworks Certified Apache Hadoop Developer can be a plus.

Practical experience in dealing with large data sets and familiarity with data warehousing and ETL tools are also important.

 

What qualities make a good Hadoop Platform Engineer?

A good Hadoop Platform Engineer is expected to have strong analytical and problem-solving skills, as they often work with complex data systems and need to find efficient solutions.

They should be comfortable dealing with large datasets and have a keen attention to detail.

Good interpersonal and communication skills are also important as they often need to collaborate with other teams and explain technical concepts in simple terms.

 

Is it difficult to hire Hadoop Platform Engineers?

Hiring Hadoop Platform Engineers can be challenging due to the specific skillset and experience required for the role.

There is a high demand for skilled engineers in the field of big data, making the hiring process competitive.

Offering competitive salaries, opportunities for professional growth, and challenging projects can attract the right talent.

 

Conclusion

And there you have it.

Today, we’ve revealed the true essence of what it means to be a Hadoop Platform Engineer.

Surprise, surprise.

It’s not just about managing data.

It’s about shaping the future of data-driven solutions, one data cluster at a time.

Armed with our detailed Hadoop Platform Engineer job description template and real-world examples, you’re ready to make your mark.

But why just stop here?

Explore further with our job description generator. It’s your stepping stone to precisely crafted job listings or sharpening your resume to ultimate precision.

Keep in mind:

Every data cluster is a piece of the larger puzzle.

Let’s construct that data-driven future. Together.

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