HBITS-07-14366-Database Architect-Expert

HBITS-07-14366-Database Architect-Expert Join to apply for the HBITS-07-14366-Database Architect-Expert role at Knowledge Builders Inc Location: Albany, New York Metropolitan Area Job Description NYSDOL Data Warehouse | UISIM project support; assist in supporting critical DOL operational functions including development, support, and optimization of data related functions within the new NYS Unemployment Insurance System. Day-to-Day Responsibilities Morning Check-in: Review overnight alerts and monitoring dashboards, check for new service requests or incidents, prioritize tasks. Communication: Respond to emails and messages, participate in daily stand-up meetings, provide updates. Documentation: Document all work performed, update knowledge base articles. DB2 Administration: Monitor performance metrics (CPU usage, memory usage, disk I/O, buffer pool hit ratios), check logs, backup/recovery processes. Maintenance: Run RUNSTATS, REORGCHK, REORG, apply patches and upgrades. Security: Review security settings and access privileges, monitor unauthorized access attempts. Model Maintenance: Update data models, ensure consistency, maintain version control. Collaboration: Work with business analysts, developers, stakeholders to review data models and requirements. Report Monitoring: Monitor Cognos reports and dashboards performance, investigate errors. Content Management: Manage Cognos content, ensure organization. User Support: Provide support for Cognos users. ETL Monitoring: Monitor ETL processes, investigate errors. Data Quality Monitoring: Monitor data quality in the warehouse, identify and correct issues. Performance Tuning: Tune Oracle database performance to optimize query response times. Data Integration: Monitor DataStage jobs, modify and update jobs as needed. Metadata Management: Review and update metadata, monitor data lineage. Data Governance: Enforce data governance policies, address compliance issues. Snowflake Data Warehouse: Monitor pipelines, troubleshoot failures, optimize queries. Artificial Intelligence: Monitor deployed AI models, collaborate with data scientists. Data Preparation: Prepare data for AI model training and deployment. Mandatory Qualifications Database Architect - Determines database structural requirements by analyzing client operations, applications, and programming; reviews objectives with clients; evaluates current systems; provides database support by coding utilities, responding to user questions, and resolving problems. Expert Experience 84+ months: Candidate is able to provide guidance to large teams and/or has extensive industry experience and is considered at the top of his/her field. Requested Qualifications 72 Months DB2, Oracle, Google Cloud Database Administration: experience in administering databases on bare metal Linux environments, including installation, configuration, performance tuning, backup/recovery, and security management. 84 Months Red Hat Linux Proficiency: experience in Red Hat Linux operating systems, including command-line administration, scripting, and system troubleshooting. 84 Months Data Modeling Experience: experience with data modeling techniques and tools, specifically Erwin Data Modeler, for designing and maintaining OLTP systems. 60 months Oracle Data Warehousing Knowledge: experience in data warehousing concepts on Oracle, DB2, or BigQuery platforms. 60 months IBM Cloud Pak for Data / Knowledge Catalog Experience: Experience implementing, managing, and utilizing IBM Cloud Pak for Data, specifically the Knowledge Catalog, for metadata management, data governance, and data lineage. 60 months Data Integration Expertise: Experience with data integration tools and techniques, particularly IBM DataStage, for designing, developing, and executing ETL processes. 84 Months IBM Cognos Analytics Skills: Experience in developing, deploying, and maintaining reports and dashboards using IBM Cognos Analytics. This includes knowledge of Cognos Framework Manager, Data Modules, Report Studio, and related components. 84 Months Snowflake Data Warehouse Experience: Experience with Snowflake Data Warehouse, including data loading, performance optimization, and query development. 84 Months AI/ML experience in Artificial Intelligence (AI) and Machine Learning (ML) concepts, data preparation, model deployment, and model monitoring. 84 Months Communication and Collaboration experience: collaborate with business analysts, developers, data scientists, and other stakeholders. Seniority Level Mid-Senior level Employment Type Full-time Job Function Information Technology #J-18808-Ljbffr