Job Description

We are seeking an experienced Data Engineer to design, build, and maintain large-scale data platforms supporting enterprise analytics and data-driven applications. The ideal candidate will have strong hands-on experience with Hadoop, Spark, containerized environments, and modern DevOps practices.

Key Responsibilities

• Design, develop, and maintain scalable data infrastructure and pipelines
• Work with large-scale data processing technologies including Hadoop and Spark
• Build and optimize data workflows for performance, reliability, and scalability
• Deploy and manage containerized data applications using Kubernetes and OpenShift
• Collaborate with DevOps teams to implement CI/CD pipelines and automation
• Monitor, troubleshoot, and optimize data platforms in production environments
• Work closely with cross-functional teams to deliver high-quality data solutions
• Ensure adherence to security, governance, and operational best practices

Requirements

• Bachelor's degree in Computer Science, Information Technology, or a related field
• At least 6 years of hands-on experience as a Data Engineer in large-scale environments
• Strong expertise in Hadoop ecosystem tools such as HDFS, Hive, Pig, Spark
• Proficiency in Python, Scala, Java, Spark, and SQL
• Experience with containerization platforms such as OpenShift Container Platform (OCP) and Kubernetes
• Knowledge of DevOps practices, CI/CD pipelines, and automation tools (Docker, Jenkins, Ansible, Bitbucket)
• Experience with job schedulers such as Control-M
• Strong problem-solving and troubleshooting skills
• Excellent communication and collaboration skills
• Ability to manage multiple priorities and deliver in a fast-paced environment

Nice to Have

• Experience with cloud platforms (AWS, Azure, or GCP) and their data services
• Exposure to Grafana, Prometheus, and Splunk
• Quantexa experience and/or certification is a strong advantage
• Experience with Elasticsearch
• Familiarity with hybrid or enterprise-scale data platforms

Key Technical Skills

Scala, Python, Spark, Java, SQL, Shell Scripting, Hadoop / Cloudera, Elasticsearch, Red Hat OpenShift (OCP)