About the Role: We are looking for a Senior Solutions Consultant with deep Hadoop knowledge and strong enterprise presence. You'll be the principal technical owner of ODP deployments - responsible not just for standing up the platform, but for guiding a customer's infrastructure, security and database teams to the right architectural decisions, and for making those decisions stick in environments where security and change control are non-negotiable. This is a hands-on role with a consultative position. You'll be equal parts architect, engineer and trusted advisor: designing the target-state cluster, executing the build, and translating hard technical trade-offs into terms a customer's stakeholders can act on. You are the person the customer relies on to get a secure, scalable platform right the first time. Product Link: https://www.acceldata.io/open-data-platform What we look for: Own cluster architecture and deployment. Lead end-to-end deployment of Acceldata ODP managed via Apache Ambari. Define cluster topology - master, slave and client node placement - sized to the customer's workload and infrastructure. Prepare and harden infrastructure. Advise on and execute OS-level prerequisites on RHEL or Ubuntu: password-less SSH, DNS/NTP, firewall ( iptables ) rules, SELinux and PackageKit handling, and system tuning such as umask and open file descriptors. Deliver secure and air-gapped deployments. Design and implement installations inside firewalled and air-gapped data centres using local mirror repositories or trusted HTTP proxy servers, working within the customer's change-control and compliance constraints. Integrate backend databases. Provision and configure operational databases (Oracle, PostgreSQL, or MySQL/MariaDB), including schemas, users and JDBC drivers for core services - Ambari, Hive, Spark, Ranger and Schema Registry. Extend the ecosystem via mpacks. Install, configure and troubleshoot components through Ambari Management Packs - Spark, Kafka, Flink, NiFi, Ozone, Airflow, Trino, ClickHouse, JupyterHub and MLflow. Implement enterprise security. Stand up cluster security end-to-end: Kerberos integration, Apache Ranger authorization policies, SSL/TLS certificate management, LDAP/AD integration, and secure credential handling (e.g. obfuscating LDAP bind passwords via the Ambari Credential Store / JCEKS). Advise and enable the customer. Run working sessions with the customer's infrastructure, security and DBA teams; document target-state architecture and handover runbooks; and coordinate with Acceldata engineering and account teams to unblock issues and drive long-term adoption. 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. Consult on design and architecture; implement strategic customer projects that lead to customers' successful understanding, evaluation, and adoption of Acceldata Data Observability Cloud. Good understanding of Data management concepts like Data Quality, Data Catalog and Data Governance . Must-Have Qualifications 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. Strongly Preferred (Great Foundation) 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.
