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AcceldataPosted 1 month ago

Senior Solutions Consultant - Open Data Platform

On-siteKitchener, Ontario, Canada

Full TimeSenior LevelMedium

Job Summary

Own cluster architecture and deployment by defining topology and sizing for customer workloads. Prepare and harden infrastructure on RHEL or Ubuntu, including OS-level prerequisites, firewall rules, and system tuning. Deliver secure and air-gapped deployments using local mirrors or trusted proxies within strict change-control constraints. Integrate backend databases and extend the ecosystem via mpacks for components like Spark, Kafka, and Trino. Implement enterprise security end-to-end, including Kerberos, Ranger, and LDAP/AD integration. Advise and enable customer infrastructure and DBA teams by documenting target-state architecture and driving adoption. This role requires 8+ years of experience in customer-facing product implementation and deep architectural knowledge of the Apache Hadoop ecosystem. Must be comfortable writing code in Java, Python, or Scala.

Required Qualifications

  • 8+ years of experience in customer-facing product implementation, designing and deploying performant end-to-end data architectures, and solving complex migrations and deployments
  • Comfortable writing code in either Java, Python or Scala
  • Deep architectural knowledge of the Apache Hadoop ecosystem (HDFS, YARN, MapReduce, Hive, ZooKeeper)
  • Strong Linux system administration on RHEL and/or Ubuntu, with a real command of network configuration, firewall rules and system tuning
  • Practical experience with enterprise security: Kerberos (KDC), SSL/TLS, LDAP/AD and Apache Ranger
  • Comfort operating within the platform's runtime stack (Java and Python) for configuration and troubleshooting
  • Excellent communication skills - able to explain hard technical trade-offs clearly to both engineers and senior stakeholders - and the autonomy to drive complex work with little supervision

Desired Qualifications

  • Extensive experience managing Cloudera (CDH/CDP) or Hortonworks (HDP) distributions - this maps to an excellent foundation for the role
  • Familiarity with several of the mpack components above (Spark, Kafka, NiFi, Trino, Ozone, MLflow, etc.) rather than all
  • Experience delivering into regulated, secured or air-gapped environments
  • Strong desire to tackle hard technical problems in Kubernetes; proven ability to do so with little or no direct daily supervision
  • Ability to quickly learn new technologies and willingness to support working in different time zones, and may be required to travel up to 50% of the time to meet with customers
  • Prior customer-facing / professional-services or consulting experience in enterprise environments

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