Big Data Developer (Hadoop Developer) Job Description Template
The Big Data Developer (Hadoop Developer) role involves designing and implementing high-performance, scalable data solutions using Hadoop ecosystems. The ideal candidate will work closely with data teams to transform structured and unstructured data into actionable insights.
Responsibilities
- Design, develop, and implement Hadoop-based solutions.
- Collaborate with data scientists and analysts to gather requirements.
- Optimize and maintain data processing frameworks.
- Develop and manage data pipelines to ensure data quality and integrity.
- Monitor Hadoop clusters and troubleshoot issues.
- Ensure data security and compliance with industry standards.
- Document technical specifications and procedures.
Qualifications
- Bachelor's degree in Computer Science, Information Technology, or a related field.
- Proven experience in Hadoop ecosystems (HDFS, HBase, Hive, Pig, etc.).
- Strong coding skills in Java, Scala, or Python.
- Knowledge of data warehousing concepts and ETL processes.
- Experience with data visualization tools (e.g., Tableau, Power BI).
- Excellent problem-solving and analytical skills.
- Strong communication and teamwork abilities.
Skills
- Hadoop
- HDFS
- Hive
- Pig
- HBase
- Spark
- Java
- Scala
- Python
- ETL
- Data Warehousing
- Data Visualization
- Data Security
Frequently Asked Questions
A Big Data Developer, often referred to as a Hadoop Developer, is responsible for designing, developing, and managing large-scale data processing systems using Hadoop. They work with technologies like HDFS, MapReduce, and Hive to help organizations process and analyze vast amounts of data efficiently. Their role includes data cleansing, transformation, and loading (ETL) processes, ensuring data reliability and integrity.
To become a Big Data Developer, one should have a solid foundation in computer science or a related field, often with a bachelor's or master's degree. Gaining expertise in Hadoop ecosystem tools such as HDFS, MapReduce, Hive, and Pig is essential. Many pursue certifications in big data technologies or attend online courses to enhance their skills and stay updated with the latest trends in data processing.
The average salary for a Big Data Developer varies based on location, experience, and employer. Generally, they earn competitive salaries due to the high demand for their skills in managing large datasets. Big Data Developers typically see salary ranges that reflect their expertise in Hadoop, data analytics, and related technologies, with those in tech hubs often earning more.
Big Data Developers typically need a degree in computer science or a related field. Certifications in big data technologies such as Hadoop, Spark, or Cloudera can give candidates an edge. Employers also look for proficiency in programming languages like Java, Python, or Scala, along with experience in data processing and analysis using Hadoop's ecosystem tools.
A Big Data Developer needs strong skills in Hadoop technologies, including HDFS, MapReduce, and Hive. They are responsible for designing and implementing complex data processes, optimizing data pipelines, and ensuring system scalability and performance. Additionally, developers must collaborate with data engineers and analysts, requiring excellent communication and problem-solving skills.