Big Data Hadoop Developer Job Description Template
The Big Data Hadoop Developer is responsible for developing, managing, and optimizing complex data pipelines using Hadoop and related technologies. You will work closely with data scientists, analysts, and engineering teams to deliver high-quality data solutions that drive business insights.
Responsibilities
- Develop, test, and maintain data pipelines using Hadoop, Hive, Pig, and related technologies.
- Collaborate with data scientists and analysts to understand data needs and deliver efficient solutions.
- Optimize and tune data processes for significant performance improvements.
- Ensure data quality and reliability through rigorous testing and validation processes.
- Implement data security measures and compliance standards.
- Document processes, procedures, and best practices for data management and analysis.
- Monitor and troubleshoot issues in the data pipeline and Hadoop ecosystem.
Qualifications
- Bachelor's degree in Computer Science, Information Technology, or related field.
- 3+ years of experience working with Hadoop and related big data technologies.
- Proven experience in designing, developing, and optimizing complex data solutions.
- Strong understanding of Hadoop architecture and ecosystem.
- Experience with Hive, Pig, Spark, and related tools.
- Familiarity with data warehousing and ETL processes.
- Strong problem-solving skills and attention to detail.
Skills
- Hadoop
- Hive
- Pig
- Spark
- HDFS
- ETL
- Data Warehousing
- SQL
- Python
- Java
Frequently Asked Questions
A Big Data Hadoop Developer is responsible for designing, building, and maintaining the complex data processing systems using Hadoop and related technologies. They manage large scale data sets, develop scripts for processing data, and work to optimize data processing performance. Their work ensures that data pipelines are efficient and scalable.
To become a Big Data Hadoop Developer, one should possess a bachelor's degree in Computer Science or a related field. Additionally, gaining expertise in Java, SQL, and NoSQL databases, along with hands-on experience with Hadoop tools like HDFS, MapReduce, and Hive, is essential. Certification in Big Data technologies can also be beneficial.
The average salary for a Big Data Hadoop Developer varies depending on experience and location. However, it typically ranges significantly as the demand for skilled developers is high. Factors influencing salary include industry, company size, and geographic location. Experienced professionals often command higher wages.
A Big Data Hadoop Developer should have a solid educational background in Computer Science, Information Technology, or a related field. Key qualifications include proficiency in Java, Python, and relevant data tools like Hadoop, Spark, and HDFS. Certifications and prior experience in handling large datasets also enhance one's qualifications.
A Big Data Hadoop Developer must have strong programming skills, particularly in Java and Python. Familiarity with Hadoop, Spark, and Pig expertise is crucial. Responsibilities include developing scalable data processing systems, troubleshooting technical issues, and optimizing data workflows. Strong analytical and problem-solving skills are essential for this role.