Senior Solutions Consultant - Hadoop/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 (open data platform) 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.

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.