Senior Solutions Consultant - Open Data Platform

**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: ### 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.