Gbolade Sgada

<p>Engineered RESTful services using Java 17, Java 21, Spring Boot 3.x, and JSON APIs, applying microservice patterns to support a controlled Spring Boot 4.0 upgrade.<br>
Containerised workloads with Docker and migrated services to ROSA on AWS and OpenShift, using Tekton pipelines and deployment checks to improve release consistency.<br>
Implemented platform migration patterns using OpenShift Pipelines and controlled cutover methods, shortening delivery cycles without introducing downtime during transition.</p>

<p>Developed a rent management platform using Spring Boot Java, Flutter, and .NET Razor, delivering 99.9% availability and supporting more than 50,000 monthly transactions.<br>
Built banking microservices using Java 17/21, Spring Boot, JDBC Template, JSON payloads, and PL/SQL stored procedures, consistently delivering sub-250ms p95 response times.<br>
Delivered service-oriented backend components using Spring Framework and microservices architecture, improving endpoint responsiveness for investment enquiry, statements, loans, and overdrafts.</p>

<p>Migrated Flexcube Oracle data into Azure Data Lake and moved an MSSQL warehouse to Snowflake, improving platform scalability for enterprise analytics workloads.<br>
Engineered ISO8583 transaction systems using Oracle, PL/SQL, C#, and .NET-linked components, processing 2M+ monthly transactions with 99.98% platform uptime.<br>
Optimised warehouse modelling using dbt and dimensional modeling methods, strengthening query performance and supporting scalable downstream reporting structures.</p>

<p>Delivered identity and access microservices using Java 17, Spring Boot, Spring Security, OAuth2, REST APIs, and JSON messaging for banking authentication journeys.<br>
Implemented ForgeRock 7.2.0 with federated authentication, MFA, and JWT-based authorisation, reducing authentication-related incidents by 40% and improving customer access reliability.<br>
Applied agile delivery methods across secure service development, supporting scalable authentication capabilities for internet and mobile banking platforms.</p>

<p>Designed ingestion pipelines using Spring Batch on Kubernetes into GCP BigQuery, reliably processing over 2M transactions per day for decision support workloads.<br>
Optimized PySpark pipelines on Azure Synapse, reducing latency to sub-3-minute processing and enabling timely decision support during high-demand periods.<br>
Implemented real-time messaging with Confluent Cloud, Kafka, and Pub/Sub patterns, increasing scalability and decoupling by approximately 50% across data flows.</p>

<p>Designed third-party data ingestion pipelines using Spring Batch, Kubernetes, and GCP BigQuery, reliably processing over 2M transactions per day.<br>
Optimized decision support pipelines using PySpark and Azure Synapse, achieving sub-3-minute latency and improving timeliness for downstream analytical workloads.<br>
Built cloud data movement patterns with Google Dataflow and Google Pub/Sub, increasing pipeline scalability and supporting resilient distributed processing.</p>

<p>Built ETL pipelines to process large volumes of text articles into PostgreSQL, supporting fast retrieval, alerts, and trend analysis across content workflows.<br>
Developed a Spring Boot microservice to serve alerts from ingested content, achieving end-to-end latency of under 5 minutes from ingestion to notification.<br>
Optimised PostgreSQL functions, indexing, and query paths using Postgres-focused delivery methods, reducing heavy analytical query execution time by 40%.</p>

<p>Built ETL jobs to process and enrich text articles into PostgreSQL, indexing metadata to support retrieval and trend analysis workflows.<br>
Optimized SQL stored procedures and deployed services on AWS, improving query responsiveness and supporting more dependable production data access.<br>
Delivered microservice-oriented data services grounded in ETL and indexing patterns, reducing manual analysis effort for downstream consumers.</p>

<p>Migrated legacy SSIS ETL jobs to Azure Data Factory, using checkpoint-enabled orchestration to improve resilience, scale, and maintainability across nightly processing.<br>
Built machine learning models using Prophet and LSTM methods for retail analytics, contributing to a 20% month-over-month revenue uplift through improved targeting.<br>
Delivered analytics modernisation using orchestration and forecasting methods, reducing nightly load times by 50% and improving recoverability for production jobs.</p>

<p>Migrated an on-premises SQL warehouse to Azure Synapse Analytics, reducing query times by 40% through cloud-based platform modernisation.<br>
Integrated Azure Data Factory and Azure Databricks for ATM journal processing, reducing processing time by 50% and improving operational throughput.<br>
Applied performance tuning across Azure-based data pipelines and warehouse workloads, improving query responsiveness and supporting scalable banking analytics.</p>

<p>Led business requirement documents for data exchange with Flexcube and T24, accelerating partner onboarding by 30% through structured stakeholder collaboration.<br>
Integrated external providers including NIBSS, credit scoring agencies, telcos, and AML services, improving credit decision precision by 18%.<br>
Coordinated partner integration deliverables using documented exchange requirements, improving clarity across internal teams and third-party onboarding workflows.</p>

<p>Built a Loan Eligibility Model using Python, TensorFlow, and Keras, integrating scoring into IVR, USSD, and mobile channels for instant decisions.<br>
Created API economy components for fintech partner integrations, streamlining connectivity with core banking systems and improving service interoperability.<br>
Delivered predictive analytics workflows using Python-based modelling and API integration methods, increasing automation across customer decisioning channels.</p>

<p>Delivered third-party integration services for loan merchants, credit scoring providers, and AML services, standardising API contracts and reducing defects by 40%.<br>
Integrated Misys Trade Finance with Flexcube using IBM IIB and WebSphere, increasing straight-through processing rates by 35% across enterprise banking flows.<br>
Authored enterprise integration patterns for partner onboarding and transaction processing, strengthening consistency across bank-facing interfaces and message exchanges.</p>

<p>Integrated Misys Trade Finance and Treasury with Oracle Flexcube using IBM Integration Bus 9, enabling straight-through processing across banking operations.<br>
Developed AI-powered mass transit applications on IBM Watson Cloud, winning a $7,000 prize in the IBM Watson Build Challenge (2018).<br>
Implemented enterprise integration flows using IBM Integration Bus methods, improving message exchange reliability between trade finance and core banking platforms.</p>

<p>Delivered information management and big data projects covering IBM Cloud, DB2 migrations, and WebSphere modernisation across multiple countries.<br>
Designed enterprise data architectures, governance models, and deployment patterns for Tier-1 banks, aligning solutions to regulatory and security standards.<br>
Applied big data and master data management methods using Hadoop, HDFS, Hive, HBase, and IBM Cognos to support enterprise information platforms.</p>

<p>Delivered big data architecture and migration programmes to DB2 and WebSphere for tier-1 clients, improving database performance by up to 40%.<br>
Ran IBM InfoSphere DataStage trainings and big data bootcamps across five universities, training more than 200 participants through hands-on engineering labs.<br>
Applied tuning, indexing, and platform optimisation methods across migration programmes, improving database performance and building practical engineering capability.</p>

<p>Led development of JEE and PL/SQL applications for contact center operations, including internet banking add-ons integrated with Flexcube, improving call deflection by 22%.<br>
Implemented an ISO8583 bridge using JPOS 1.5 on JDK 1.6 to integrate with Flexcube, increasing transaction reliability and throughput during peak periods.<br>
Delivered operational banking services with JEE and PL/SQL methods, reducing branch dependency and supporting more reliable customer service workflows.</p>

<p>Led development of applications and services using JEE and PL/SQL for contact center operations, internet banking modules, and SMS alerting.<br>
Built an ISO8583 bridge to Flexcube with JPOS 1.5, enabling reliable transaction processing and message translation across banking systems.<br>
Delivered integration-focused service components using Spring Boot-linked and PL/SQL grounded methods, improving operational consistency for customer-facing banking services.</p>

<p>Led core service upgrades using Spring Boot 3.5, Spring Security 6, and Java 17/21, resolving compatibility issues to stabilise releases and reduce post-release defects.</p><p> Developed a JAX-RS and Jackson service in Java 17, integrating with DB2 through key exchange authentication to support benefits and payments processing.</p><p> Delivered application modernisation using grounded upgrade and serialization patterns, improving production stability and reducing mean time to recovery during releases.</p>

<p>Architected analytics datasets using Microsoft Fabric, Power Query, and dataflows, standardising ETL and incremental refresh to support governed reporting aligned to report SLOs.</p><p> Established CI/CD across Dev, Test, and Prod using Git-based versioning and configuration validation, improving release control and consistency across three environments.</p><p> Implemented governed reporting patterns using Power BI, DAX, RLS, and SCD-aligned datasets, increasing visibility and supporting dependable refresh operations.</p>

<p>Developed backend RESTful services in Java with OAuth-compliant authentication and OWASP-aligned controls, hardening API endpoints to strengthen application security.</p><p> Integrated Meta-Llama, Llama-3.3-70B-Instruct, Hugging Face, and OpenAI APIs into services, delivering domain-tuned recommendations through grounded LLM-enabled workflows.</p><p> Authored tested service components using JUnit and Mockito, supporting secure feature delivery and improving maintainability across backend integrations.</p>