Data Engineer II

• Develop and implement complex database designs to support the organization's big data initiatives. • Perform advanced SQL queries for reporting purposes using Oracle Database Management System tools. • Monitor system performance metrics such as CPU usage, memory consumption, disk space utilization, etc., on a regular basis (daily or weekly). • Collaborate with cross-functional teams to understand data needs and develop solutions that meet business requirements while ensuring the integrity of company databases. • Maintain database security by implementing best practices for access control policies based on user roles within an organization, including but not limited to: creating users/groups; assigning permissions (reads, writes); setting up audit trails using Oracle Auditing tools and features such as Fine Grained Access Control (FGAC). • Perform routine backups of databases with a focus on minimizing downtime during the backup process. Backup strategies should include full database dumps followed by incremental or differential backups, along with offsite storage for disaster recovery purposes using Oracle RMAN and other tools as needed (e.g., AWS S3). • Troubleshoot performance issues in databases to ensure optimal system efficiency; this may involve analyzing query execution plans, identifying bottlenecks or resource contention points within the database environment, optimizing SQL queries for better response times using Oracle's Explain Plan and other tools as needed. • Develop custom scripts/tools (e.g., Python) to automate repetitive tasks such as data extraction from multiple sources; these should be well documented with comments explaining their purpose and usage instructions provided in a shared repository accessible by cross-functional teams for collaboration purposes using version control systems like Git or SVN, along with proper testing procedures before deployment. • Stay up to date on emerging technologies related to data engineering such as Apache Spark, Hadoop ecosystems (e.g., YARN), and NoSQL databases; this may involve attending industry conferences/workshops, participating in online forums or communities of practice, reading relevant publications from reputable sources like MIT Technology Review or IEEE Spectrum to keep skills current with best practices as they evolve over time. • Communicate effectively with cross-functional teams including business analysts and IT professionals; this may involve regular meetings/presentations using tools such as Zoom, Microsoft Teams, Google Meet etc., along with providing clear documentation on data models or reports generated for easy interpretation by non-technical stakeholders. • Maintain a high level of proficiency in SQL and other relevant programming languages (e.g., Python) through continuous learning opportunities such as online courses, certifications from reputable sources like Coursera/Udacity etc.; this may involve setting personal goals for skill development within