• At least 6 years of experience as a Data Engineer, working with Hadoop, Spark, and data processing technologies in large-scale environments

• Strong expertise in designing and developing data infrastructure using Hadoop, Spark, and related tools (HDFS, Hive, Pig, etc)

• Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration using Kubernetes

• Proficiency in programming languages commonly used in data engineering, such as Spark, Python, Scala, or Java

• Knowledge of DevOps practices, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)

• Experience with jobs schedulers like Control-m

• Experience with Graphana, Prometheus, Splunk will be an added benefit

• Quantexa exposure and/or certification a strong plus

• Strong problem-solving and troubleshooting skills with a proactive approach to resolving technical challenges

• Excellent collaboration and communication skills to work effectively with cross-functional teams

• Ability to manage multiple priorities, meet deadlines, and deliver high-quality results in a fast-paced environment

• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services is a plus

Data Engineer