Highlights
Work with industry leaders, global customers, learn from experts, and contribute to mission-critical projects.
Description
Job Summary
pJoin Acceldata, the market leader in Enterprise Data Observability. As an Associate Product Support Engineer, you will support Hadoop data lake environments, assist with complex migrations, and provide expert-level troubleshooting for our global customers.
Responsibilities
- Support cluster operations of Hadoop data lake clusters (HDFS, YARN, Hive/Impala)
- Assist in diagnosing issues across the entire stack, including hardware, software, applications (Spark, NiFi), and networks
- Participate in performance tuning to optimize data processing jobs for low-latency and high-throughput performance
- Provide dedicated support during and after migrations to ensure system reliability
- Listen actively to customer concerns and provide technical solutions in a 24/7 global support environment
Required Skills
- Hadoop stack knowledge (HDFS, YARN, Hive/Impala)
- Linux command-line proficiency
- Scripting experience in Python, Bash, or Scala
- Experience with distributed systems and cloud environments
- Problem-solving skills and attention to detail
Required Skills Explained
- 1-3 years of experience in distributed systems, cloud environments, or data management services.
- Good understanding of HDFS, YARN, and Hive/Impala.
- Working knowledge of Kafka, NiFi, and Cloudera Manager is a plus.
- Strong command-line skills for configuring and troubleshooting RedHat and Debian-based distributions.
- Experience with scripting languages such as Python, Bash, or Scala for automation and debugging.
Who is this for
pThis role is ideal for junior professionals seeking to master large-scale distributed systems and work alongside senior engineers. You should have a passion for data management and troubleshooting complex issues.
Why This Job is a Good Opportunity
ulliJoin the market leader in Enterprise Data Observability, contributing to innovative technology solutions.liPotential to work on mission-critical projects that impact global enterprises directly.liOpportunity to collaborate with senior engineers and gain hands-on experience in large-scale distributed systems.liDiverse role that combines technical challenges with customer support, offering a well-rounded professional development path.
Interview Preparation Tips
- Research Acceldata's products and technology stack thoroughly.
- Prepare examples of your experience with Hadoop and data management systems.
- Showcase your problem-solving skills through relevant case studies or projects.
- Briefly explain how you handle shift work flexibility in a supportive manner.
Career Growth in This Role
pThe role offers significant opportunities for career growth, especially as an Associate Product Support Engineer. As you build expertise and demonstrate reliability, Acceldata may offer advanced roles such as Senior Product Support Engineer or even move into product management positions within the company. The technical skills gained are highly valued across various tech sectors.pFurther development could include specializations in specific areas like data operations, system optimization, or customer support leadership, depending on your interests and performance. The continuous learning environment at Acceldata encourages employees to stay updated with the latest industry trends and technologies, fostering a dynamic career trajectory.
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Skills
Frequently Asked Questions
What is the role of this position?You will be responsible for supporting Hadoop data lake clusters, assisting with migrations, and providing technical support to global customers.
What technical skills are required?Hadoop stack knowledge (HDFS, YARN, Hive/Impala), Linux command-line proficiency, scripting experience in Python, Bash, or Scala.
Is this role suitable for beginners?Yes, it is designed for junior professionals with a passion to learn and work alongside senior engineers. One to three years of experience in distributed systems, cloud environments, or data management services is preferred.
