Fredy Soussou

Led and grew a geographically distributed database engineering team of 8 across 3 time zones (North America, Europe, APAC).
Established structured on-call rotations, standardized runbook documentation, mentorship programs, and incident escalation protocols.
Reduced escalations by 64% and measurably improved mean-time-to-resolve (MTTR) across production environments.
Engineered a 340% scale-up of the SQL Server data platform to support explosive growth in real-time gaming transactions across 12 countries.
Sustained 99.97% uptime across 47 production databases through proactive capacity planning, performance engineering, and automated monitoring.
Led end-to-end migration of 23 SQL Server instances to Always On Availability Groups (AOAG).
Reduced mean recovery time from 4 hours to 12 minutes and enabled non-disruptive failover across multi-region environments.
Architected and delivered a cloud migration initiative to AWS RDS for key customer-facing database workloads.
Scoped infrastructure requirements, led phased cutover planning, coordinated with client technical teams, and ensured zero data loss during transition to cloud infrastructure.
Diagnosed critical query bottlenecks at peak traffic.
Applied execution plan analysis, index optimization, and T-SQL rewrites.
Reduced average query response time by 92% from 2.4s to 180ms and eliminated production-impacting incidents.
Built and deployed Databricks-based PySpark ETL pipelines and Python automation scripts to streamline high-volume gaming transaction data workflows across multi-region SQL Server environments.
Replaced manual batch processes and enabled scalable, repeatable data transformation at enterprise scale.
Designed and delivered Power BI dashboards for internal stakeholders and external client-facing reporting.
Enabled real-time visibility into platform KPIs, SLA compliance, and transaction throughput across 12 countries.
Led external client-facing technical engagements including architecture reviews, data platform demos, and migration planning sessions with enterprise customers.
Served as the primary technical point of contact for cross-regional data platform discussions and project scoping.
Managed and administered diverse database environments including PostgreSQL, MongoDB, and NoSQL alongside SQL Server.
Designed schemas, tuned queries, enforced access controls, and ensured data integrity across polyglot persistence architectures.
Automated 18 manual database deployment and maintenance workflows using PowerShell and Python.
Cut release cycle time from 6 hours to 45 minutes and reduced deployment-related incidents by 78%.
Integrated AI tools to accelerate development and operational workflows.
Leveraged Microsoft Copilot for code generation, documentation drafting, and SQL query acceleration.
Used Claude AI for complex data pipeline design, technical analysis, and automating repetitive engineering tasks.
Designed and validated DR architecture for Tier-1 systems achieving RPO of 5 minutes and RTO of 15 minutes.
Confirmed results through quarterly DR drills and continuous HA/DR refinement cycles.

Led and grew a geographically distributed database engineering team of 8 across 3 time zones, Engineered a 340% scale-up of the SQL Server data platform, Eliminated single points of failure by leading end-to-end migration of 23 SQL Server instances to Always On Availability Groups (AOAG), Architected and delivered a cloud migration initiative to AWS RDS, Diagnosed critical query bottlenecks at peak traffic, Built and deployed Databricks-based PySpark ETL pipelines and Python automation scripts, Designed and delivered Power BI dashboards for internal stakeholders and external client-facing reporting, Spearheaded external client-facing technical engagements, Managed and administered diverse database environments including PostgreSQL, MongoDB, and NoSQL alongside SQL Server, Automated 18 manual database deployment and maintenance workflows using PowerShell and Python, Accelerated development and operational workflows by integrating AI tools, Designed and validated DR architecture for Tier-1 systems

Built, mentored, and managed a cross-functional development and database team of 5 engineers.
Delivered technical leadership across 14 integration projects.
Defined coding standards, conducted code reviews, and drove Agile sprint planning across benefits, HR, and payroll platforms.
Consolidated 37 fragmented data models across 12 HR applications into a unified enterprise database architecture.
Reduced data inconsistencies by 91% and enabled real-time reporting for 2.3 million employee records.
Executed zero-downtime migration of 8 mission-critical benefits administration systems during open enrollment periods serving 500K+ users.
Applied phased cutover strategies and pre-validated rollback procedures with zero data loss.
Replaced Oracle-based legacy pension calculation database with SQL Server.
Eliminated $180K in annual licensing costs while improving calculation performance by 240% through stored procedure rewriting, schema redesign, and index optimization.
Built Python and PySpark data transformation pipelines to automate benefits data processing and cross-system reconciliation across 12 integrated HR applications.
Reduced large-dataset processing time and enabled analytics at scale for 2.3M employee records.
Led technical database delivery for 14 cross-functional integration projects connecting HR, payroll, and benefits platforms using SSIS, T-SQL, and custom stored procedures.
Established reusable integration patterns that accelerated subsequent delivery by 60%.

Built, mentored, and managed a cross-functional development and database team of 5 engineers, Consolidated 37 fragmented data models across 12 HR applications into a unified enterprise database architecture, Executed zero-downtime migration of 8 mission-critical benefits administration systems, Replaced Oracle-based legacy pension calculation database with SQL Server, Built Python and PySpark data transformation pipelines, Led technical database delivery for 14 cross-functional integration projects

Resolved a critical reporting bottleneck in manufacturing software by redesigning the index strategy and rewriting core T-SQL queries.
Reduced report generation time from 8 minutes to 22 seconds.
Achieved a 95% improvement with zero production impact.
Architected real-time data synchronization across 6 manufacturing facilities using SSIS.
Enabled live production visibility and data-driven operational decisions globally.
Replaced static Excel-based reporting with a self-service SSRS portal.
Gave 50+ stakeholders real-time access to production metrics at sub-second refresh rates.

Designed SQL Server architecture including stored procedures, tables, and views.
Built a custom reporting system using the SharpShooter engine.
Enabled real-time contract analytics and BI for stakeholders.
Developed contract and leads management applications in C# and VB.NET.
Automated key business workflows and significantly reduced manual processing overhead.