Cloudera Data Platform Engineer
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Summary
Manage, monitor, and optimize Cloudera Data Platform environments (HDFS, YARN, HIVE, Spark, Impala, Ranger) using monitoring tools like Cloudera Manager/Grafana/Splunk and automation via bash/Python scripting, with middleware integration (Informatica, Denodo).
We are looking for a skilled
Cloudera Data Platform Engineer
to join our dynamic team. The ideal candidate will have hands-on experience with
Cloudera Data Platform components
such as
HDFS, YARN, HIVE, Spark, Impala, Ranger , along with strong knowledge of
operating systems, security, and networking . You will be responsible for monitoring, troubleshooting, and optimizing big data environments using advanced tools and automation scripts. Key Responsibilities:
Cloudera Data Platform Management: Manage and troubleshoot components of the
Cloudera Data Platform , including at least three of the following:
HDFS, YARN, HIVE, Spark, Impala, Ranger . Ensure the security and integrity of data within the platform. Optimize performance and resource utilization across the data ecosystem. Monitoring and Troubleshooting: Utilize monitoring tools such as
Cloudera Manager, Zabbix, Grafana, Splunk, and SyslogNG
for proactive system monitoring and incident management. Perform root cause analysis and implement corrective actions to ensure high availability and reliability of data systems. Automation and Scripting: Develop and maintain automation scripts using
bash, Python, or shell scripting
to streamline operational tasks. Implement automated solutions for system provisioning, monitoring, and maintenance. Middleware and Integration: Collaborate with middleware applications such as
Informatica
and
Denodo
to ensure seamless data integration and processing. Ensure compatibility and integration with other enterprise systems. Cloud Technology Exposure (Optional): Work with
cloud technologies (AWS, Azure)
for data storage, processing, and migration (if applicable). Collaborate with cloud architects to optimize data solutions in hybrid cloud environments. Requirements:
Technical Skills: Hands-on experience with at least
three components
of the
Cloudera Data Platform :
HDFS, YARN, HIVE, Spark, Impala, Ranger . Proficiency with
monitoring tools
like
Cloudera Manager, Zabbix, Grafana, Splunk, and SyslogNG . Strong skills in
scripting languages
such as
bash, Python, or shell scripting
for automation and process optimization. Familiarity with
middleware applications
like
Informatica
and
Denodo . Basic understanding of
operating systems, security, and network
configurations. Experience: 5+
in managing and troubleshooting Cloudera Data Platform environments. Experience in
monitoring and incident management
using advanced monitoring tools. Knowledge of
cloud technologies (AWS, Azure)
is a plus. Soft Skills: Strong problem-solving and analytical skills. Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment. Ability to manage multiple tasks and prioritize effectively in a fast-paced environment. Preferred Qualifications:
Certification in
Cloudera Data Platform
or related big data technologies. Experience with
cloud technologies (AWS, Azure)
for data storage and processing. Familiarity with
big data frameworks
and ecosystems.
Cloudera Data Platform Engineer
to join our dynamic team. The ideal candidate will have hands-on experience with
Cloudera Data Platform components
such as
HDFS, YARN, HIVE, Spark, Impala, Ranger , along with strong knowledge of
operating systems, security, and networking . You will be responsible for monitoring, troubleshooting, and optimizing big data environments using advanced tools and automation scripts. Key Responsibilities:
Cloudera Data Platform Management: Manage and troubleshoot components of the
Cloudera Data Platform , including at least three of the following:
HDFS, YARN, HIVE, Spark, Impala, Ranger . Ensure the security and integrity of data within the platform. Optimize performance and resource utilization across the data ecosystem. Monitoring and Troubleshooting: Utilize monitoring tools such as
Cloudera Manager, Zabbix, Grafana, Splunk, and SyslogNG
for proactive system monitoring and incident management. Perform root cause analysis and implement corrective actions to ensure high availability and reliability of data systems. Automation and Scripting: Develop and maintain automation scripts using
bash, Python, or shell scripting
to streamline operational tasks. Implement automated solutions for system provisioning, monitoring, and maintenance. Middleware and Integration: Collaborate with middleware applications such as
Informatica
and
Denodo
to ensure seamless data integration and processing. Ensure compatibility and integration with other enterprise systems. Cloud Technology Exposure (Optional): Work with
cloud technologies (AWS, Azure)
for data storage, processing, and migration (if applicable). Collaborate with cloud architects to optimize data solutions in hybrid cloud environments. Requirements:
Technical Skills: Hands-on experience with at least
three components
of the
Cloudera Data Platform :
HDFS, YARN, HIVE, Spark, Impala, Ranger . Proficiency with
monitoring tools
like
Cloudera Manager, Zabbix, Grafana, Splunk, and SyslogNG . Strong skills in
scripting languages
such as
bash, Python, or shell scripting
for automation and process optimization. Familiarity with
middleware applications
like
Informatica
and
Denodo . Basic understanding of
operating systems, security, and network
configurations. Experience: 5+
in managing and troubleshooting Cloudera Data Platform environments. Experience in
monitoring and incident management
using advanced monitoring tools. Knowledge of
cloud technologies (AWS, Azure)
is a plus. Soft Skills: Strong problem-solving and analytical skills. Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment. Ability to manage multiple tasks and prioritize effectively in a fast-paced environment. Preferred Qualifications:
Certification in
Cloudera Data Platform
or related big data technologies. Experience with
cloud technologies (AWS, Azure)
for data storage and processing. Familiarity with
big data frameworks
and ecosystems.