To help you prepare for job searching or hiring, here are trending job titles and descriptions for working in the Hadoop field. Please keep in mind, these are only samples.
Hadoop Developer
Responsibilities:
- Designing, developing, testing, and maintaining Hadoop applications and solutions.
- Writing high-quality code using programming languages such as Java, Scala, or Python.
- Collaborating with cross-functional teams to understand business requirements and translate them into technical solutions.
- Optimizing Hadoop jobs and queries for performance and scalability.
- Troubleshooting and resolving issues related to Hadoop cluster operations.
- Implementing security measures and ensuring data integrity within the Hadoop environment.
Requirements:
- Proficiency in programming languages like Java, Scala, or Python.
- Hands-on experience with Hadoop ecosystem technologies such as HDFS, MapReduce, Hive, Pig, and Spark.
- Strong understanding of distributed computing principles and data processing frameworks.
- Knowledge of SQL and NoSQL databases.
- Familiarity with data warehousing concepts and ETL processes.
- Excellent problem-solving and analytical skills.
- Good communication and teamwork abilities.
Hadoop Administrator
Responsibilities:
- Installing, configuring, and maintaining Hadoop clusters and related tools.
- Monitoring and managing the performance, capacity, and security of Hadoop environments.
- Troubleshooting and resolving system and application issues.
- Implementing backup, recovery, and disaster recovery strategies for Hadoop systems.
- Collaborating with cross-functional teams to plan and execute Hadoop upgrades and patches.
- Ensuring data integrity, availability, and reliability within the Hadoop infrastructure.
Requirements:
- Strong experience in Hadoop cluster administration and management.
- Proficiency in Linux/Unix systems and shell scripting.
- Familiarity with Hadoop ecosystem components such as HDFS, YARN, MapReduce, Hive, and HBase.
- Knowledge of network configuration, security, and troubleshooting.
- Understanding of storage systems and distributed file systems.
- Experience with monitoring and performance tuning of Hadoop clusters.
- Excellent problem-solving and communication skills.
- Ability to work independently and handle multiple tasks.
Hadoop Data Engineer
Responsibilities:
- Designing and developing data ingestion pipelines and workflows in Hadoop.
- Building and maintaining data processing and transformation frameworks using technologies like Spark, Kafka, or Flink.
- Implementing data quality and data governance processes within the Hadoop ecosystem.
- Collaborating with data scientists and analysts to define data requirements and develop data models.
- Optimizing data storage and retrieval processes for performance and scalability.
- Monitoring and troubleshooting data processing and integration jobs.
Requirements:
- Strong programming skills in languages like Java, Scala, or Python.
- Proficiency in Hadoop ecosystem technologies such as HDFS, MapReduce, Spark, Kafka, or Flink.
- Experience with data integration and ETL tools.
- Knowledge of SQL and NoSQL databases.
- Familiarity with data warehousing concepts and dimensional data modeling.
- Understanding of data governance and data quality principles.
- Good analytical and problem-solving abilities.
- Strong communication and collaboration skills.
Hadoop Architect
Responsibilities:
- Designing and implementing end-to-end Hadoop-based solutions, considering scalability, reliability, and performance.
- Defining system architectures and data models to meet business requirements.
- Evaluating and selecting appropriate Hadoop ecosystem components and tools.
- Providing technical guidance and mentorship to development teams.
- Collaborating with stakeholders to understand business needs and translate them into technical solutions.
- Ensuring data security, integrity, and compliance within the Hadoop environment.
Requirements:
- Significant experience as a Hadoop architect or a similar role.
- Deep understanding of the Hadoop ecosystem, including HDFS, YARN, MapReduce, Hive, Spark, and related technologies.
- Proficiency in programming languages such as Java, Scala, or Python.
- Knowledge of data modeling, data integration, and ETL processes.
- Familiarity with cloud platforms and distributed computing frameworks.
- Strong problem-solving and decision-making skills.
- Excellent communication and leadership abilities.
- Ability to work collaboratively with cross-functional teams.
Hadoop Big Data Engineer
Responsibilities:
- Designing and implementing large-scale big data solutions using Hadoop and related technologies.
- Building data pipelines and workflows to ingest, process, and analyze massive datasets.
- Developing and optimizing MapReduce or Spark jobs for data processing and transformation.
- Designing and managing data storage systems, including Hadoop Distributed File System (HDFS).
- Ensuring data quality, integrity, and availability within the big data infrastructure.
- Collaborating with data scientists and analysts to define data requirements and develop analytics solutions.
Requirements:
- Strong experience in big data engineering with Hadoop and related technologies.
- Proficiency in programming languages like Java, Scala, or Python.
- In-depth knowledge of Hadoop ecosystem components such as HDFS, MapReduce, Hive, Spark, or Kafka.
- Familiarity with data integration, ETL, and data warehousing concepts.
- Understanding of distributed computing principles and cloud-based infrastructure.
- Experience with data modeling and data management techniques.
- Excellent problem-solving and analytical skills.
- Strong communication and teamwork abilities.
Hadoop Analyst
Responsibilities:
- Analyzing and interpreting large datasets using Hadoop and associated tools.
- Developing data queries, reports, and visualizations to present insights to stakeholders.
- Collaborating with business users to define data analysis requirements and objectives.
- Identifying patterns, trends, and anomalies in data to support decision-making.
- Conducting data profiling and data quality assessment within the Hadoop ecosystem.
- Supporting data governance and compliance initiatives.
Requirements:
- Proficiency in Hadoop ecosystem technologies such as HDFS, Hive, Pig, or Spark.
- Strong SQL and data querying skills.
- Experience with data analysis and visualization tools.
- Knowledge of statistical analysis and data mining techniques.
- Familiarity with data governance and data quality principles.
- Excellent problem-solving and analytical skills.
- Good communication and presentation abilities.
- Strong attention to detail and data accuracy.
Hadoop Data Scientist
Responsibilities:
- Leveraging Hadoop and big data technologies to perform advanced analytics and machine learning tasks.
- Developing and implementing predictive models, algorithms, and data mining techniques.
- Collaborating with cross-functional teams to identify and define business problems that can be addressed through data analysis.
- Extracting and transforming data from Hadoop environments for analysis and modeling.
- Presenting findings and insights to stakeholders in a clear and actionable manner.
- Staying up-to-date with the latest advancements in data science and big data technologies.
Requirements:
- Strong background in data science, statistics, or a related field.
- Proficiency in programming languages like Python, R, or Scala.
- Experience with Hadoop ecosystem technologies such as HDFS, Hive, Spark, or Pig.
- Knowledge of machine learning algorithms and techniques.
- Familiarity with data visualization and reporting tools.
- Strong analytical and problem-solving skills.
- Excellent communication and storytelling abilities.
- Ability to work collaboratively and translate business requirements into data-driven solutions.
Hadoop Solution Architect
Responsibilities:
- Designing end-to-end Hadoop-based solutions that meet business requirements.
- Assessing existing systems and infrastructure to identify opportunities for integrating Hadoop.
- Collaborating with stakeholders to define solution architecture and technical specifications.
- Evaluating and selecting appropriate Hadoop ecosystem components and tools.
- Providing guidance and support to development teams during solution implementation.
- Ensuring the scalability, reliability, and security of Hadoop solutions.
Requirements:
- Significant experience as a solution architect or a similar role.
- Deep understanding of the Hadoop ecosystem, including HDFS, YARN, MapReduce, Hive, Spark, and related technologies.
- Knowledge of data integration, ETL, and data warehousing concepts.
- Familiarity with cloud platforms and distributed computing frameworks.
- Strong problem-solving and decision-making skills.
- Excellent communication and leadership abilities.
- Ability to work collaboratively with cross-functional teams.
Hadoop Operations Manager
Responsibilities:
- Overseeing the day-to-day operations of Hadoop clusters and associated systems.
- Monitoring system performance, capacity, and availability.
- Planning and executing cluster upgrades, patches, and maintenance activities.
- Troubleshooting and resolving issues related to cluster operations and performance.
- Implementing and enforcing security measures and best practices.
- Collaborating with cross-functional teams to define operational requirements and improve system efficiency.
Requirements:
- Strong experience in managing Hadoop clusters and associated systems.
- Proficiency in Linux/Unix systems and shell scripting.
- In-depth knowledge of Hadoop ecosystem components and tools.
- Familiarity with network configuration, security, and troubleshooting.
- Understanding of storage systems and distributed file systems.
- Experience with monitoring and performance tuning of Hadoop clusters.
- Strong problem-solving and communication skills.
- Ability to work independently and handle multiple tasks.
Hadoop Platform Engineer
Responsibilities:
- Designing, building, and maintaining Hadoop platforms and infrastructure.
- Collaborating with cross-functional teams to define platform requirements and architectures.
- Implementing and managing Hadoop clusters and associated tools.
- Developing automation scripts and tools for system provisioning, configuration, and monitoring.
- Ensuring platform security, performance, and scalability.
- Troubleshooting and resolving issues related to Hadoop platform and infrastructure.
Requirements:
- Strong experience in building and managing Hadoop platforms.
- Proficiency in Linux/Unix systems and shell scripting.
- In-depth knowledge of Hadoop ecosystem components such as HDFS, YARN, MapReduce, Hive, and Spark.
- Familiarity with cloud platforms and containerization technologies.
- Experience with infrastructure automation and configuration management tools.
- Understanding of network configuration, security, and troubleshooting.
- Strong problem-solving and communication skills.
- Ability to work collaboratively and handle multiple projects.
Please note that the above job titles and descriptions are provided as samples only.