Oracle Database Administrator

Lanteris Space Systems•Mountain View, CA

2d•$124,000 - $238,000•Remote

About The Position

Lanteris Space is a leading provider of comprehensive space technologies. We deliver innovative solutions to government and commercial customers helping them unlock the promise of space to solve problems on Earth and beyond. We address a broad spectrum of needs for our customers, including mission systems engineering, product design, spacecraft manufacturing, assembly, integration and testing. Lanteris Space Systems is a trusted partner in commercial and government missions, combining more than 60 years of deep mission understanding with reliable performance and longevity. We are seeking an experienced Oracle Database Administrator to join our IT team. This role can be based in our Bay area offices or can be performed remotely. In this role, you will be responsible for the design, implementation, maintenance, and optimization of our Oracle database systems that support our spacecraft design, manufacturing, and mission operations. As we expand our AI and machine learning capabilities, this role offers opportunities to evolve into data engineering responsibilities supporting AI/ML initiatives.

Requirements

Must be a US Citizen or permanent resident
Bachelor's degree in Computer Science, Information Systems, or related field. Four additional years of experience may be substituted for a degree
8 years of experience as an Oracle Database Administrator
Experience with Oracle Database (including 9i, 11g, 12c, 19c, or 21c)
Experience with Oracle performance tuning and optimization (AWR, ASH, SQL Tuning Advisor)
Knowledge of Oracle backup/recovery procedures (RMAN, Data Guard)
Experience with Oracle database security and user management
Experience with SQL and PL/SQL programming skills
Understanding of database security best practices

Nice To Haves

Experience in aerospace, defense, or manufacturing environments
Oracle Certified Professional (OCP) or Oracle Certified Master (OCM) certification
Experience with Oracle Real Application Clusters (RAC)
Experience with Oracle Exadata or Autonomous Database
Experience supporting legacy Oracle 9i environments and migration planning
Knowledge of other RDBMS platforms (SQL Server, PostgreSQL, MySQL)
Knowledge of cloud database services (Oracle Cloud Infrastructure, AWS RDS)
Familiarity with NoSQL databases (MongoDB, Cassandra)
Experience with database automation and Infrastructure as Code
Experience with data warehouse and business intelligence systems (Oracle Data Warehouse)
Understanding of ITAR/EAR compliance requirements
Experience with data pipeline tools (Apache Airflow, AWS Glue, Azure Data Factory, Oracle Data Integrator)
Knowledge of vector databases or databases optimized for AI workloads
Familiarity with data versioning and MLOps practices
Experience with large-scale data processing frameworks (Spark, Hadoop)
Understanding of data requirements for training and deploying machine learning models
Strong problem-solving and analytical skills
Excellent communication and documentation abilities
Willingness to learn and adapt to data engineering practices supporting AI/ML initiatives

Responsibilities

Design, implement, and maintain Oracle database systems (primary focus)
Monitor Oracle database performance, optimize queries, and tune systems for maximum efficiency
Develop and execute backup and disaster recovery strategies for Oracle environments
Implement and maintain database security policies and access controls
Manage Oracle database architecture, including RAC, Data Guard, and ASM
Collaborate with software engineers and systems administrators on database design
Perform Oracle database migrations, upgrades, and patches
Troubleshoot database issues and provide technical support
Create and maintain documentation for database configurations and procedures
Ensure compliance with data governance and regulatory requirements
Support both on-premises and cloud-based Oracle database environments (OCI, AWS RDS for Oracle)
Work with data science and AI teams to design and optimize data pipelines for machine learning workloads
Support data lake and data warehouse architectures that enable AI/ML model training and inference