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Excellent onboarding and industry-leading learning culture will set you up for a positive impact while advancing your career. Our culture is collaborative and experiential. As part of a team you will be surrounded by bright minds and keen co-creators—always willing to help and be helped—as you apply passion to work that will positively impact the world around us.
We are seeking a highly skilled and experienced Spark Cluster Admin to join our dynamic team. This role is critical for building optimizing and supporting our cutting-edge data platform leveraging Apache Spark Apache Iceberg and a robust DevOps approach within an OpenShift environment. The ideal candidate will be adept at both developing high-performance data solutions and ensuring their stability and reliability in a production setting.
Key Responsibilities
- Design develop and optimize scalable and resilient data processing applications using Apache Spark (batch streaming and real-time).
- Implement and manage data pipelines ensuring data quality consistency and performance.
- Perform Spark job performance tuning and optimization to handle large-scale datasets efficiently.
- Manage and automate the deployment of Spark applications within OpenShift clusters utilizing Docker and Kubernetes.
- Establish and maintain CI/CD pipelines for automated testing deployment and release management of Spark workloads.
- Provide comprehensive production support for critical Spark jobs including proactive monitoring troubleshooting debugging and participation in on-call rotations.
- Work extensively with Apache Iceberg table format leveraging its capabilities for schema evolution time travel hidden partitioning and ACID transactions.
- Collaborate closely with data scientists other data engineers and operations teams to deliver robust and integrated solutions.
- Develop and maintain documentation for data pipelines job configurations and operational procedures.
- 9+ years of hands-on experience in Spark cluster administration roles.
- Expert-level proficiency in Apache Spark (Spark Core Spark SQL Spark Streaming).
- Strong programming skills in Scala Python (PySpark) or Java .
- Significant experience with OpenShift including deploying managing and automating containerized applications within the platform.
- Solid understanding of Docker and Kubernetes for containerization and orchestration.
- Proven experience implementing and maintaining CI/CD pipelines using tools like Jenkins GitLab CI or similar.
- Demonstrable experience with Apache Iceberg including practical application of its features like schema evolution time travel queries and ACID compliance.
- Strong background in production support for data applications including monitoring troubleshooting and incident resolution.
- Understanding and practical application of DevOps principles (Infrastructure as Code automation continuous monitoring).
- Strong SQL skills and experience working with various data sources.
- Excellent analytical and problem-solving abilities for diagnosing and resolving complex issues in distributed environments.
- Familiarity with distributed systems concepts and architectures.
- Experience with other data lake table formats (e.g. Delta Lake Apache Hudi).
- Familiarity with cloud platforms (AWS Azure GCP) beyond OpenShift.
- Experience with messaging queues or streaming platforms like Apache Kafka.
- Contributions to open-source data projects.