Machine Learning Data Engineer

TAYO OSESINA

Staff Engineer - MLOps / Cloud Solution Architect

Hagerstown, MD 21742 301-***-**** ********@*****.*** LinkedIn Profile EXECUTIVE PROFILE

Staff Data Engineer and Distributed Systems Architect with 12+ years of experience leading the design and delivery of large-scale, mission-critical data infrastructure. Proven expertise in architecting high-throughput, low-latency platforms that support billions of transactions daily across hybrid and multi-cloud environments. Deeply skilled in both structured and unstructured data systems, data processing, data explorations, data modelling and Machine Learning Operations

Certified AWS Solutions Architect Professional with a strong foundation in cloud-native architecture, infrastructure-as-code, Kubernetes orchestration, and performance-driven DevOps. Adept at aligning engineering strategy with business goals by building resilient, scalable systems that enhance developer velocity, ensure data reliability, and reduce operational overhead.

Trusted technical leader in high-stakes, regulated environments—recognized for setting platform standards, driving cross-team alignment, mentoring engineers, and guiding architectural decisions that enable long-term scalability, observability, and innovation. CORE EXPERTISE

Data Infrastructure Cloud & DevOps Leadership & Strategy Database Architecture &

Scaling

Multi-Cloud Infrastructure Technical Mentorship

Distributed Systems Design Infrastructure as Code Requirements Analysis High-Availability Solutions Containerization &

Orchestration

Cross-Functional

Collaboration

Performance Optimization CI/CD Automation Project Planning & Execution Disaster Recovery Strategy Observability & Monitoring Architecture Review & Governance

TECHNICAL PROFICIENCIES

Data Management

● Relational: PostgreSQL, MySQL, Aurora, Oracle (10+ years)

● NoSQL: MongoDB, Cassandra, DynamoDB, Redis (8+ years)

● Analytics: Elasticsearch, OpenSearch, Druid, Trino (5+ years)

● Streaming: Kafka, Pulsar, Kinesis (3+ years)

Cloud & Infrastructure

● AWS: RDS, EC2, S3, DynamoDB, EKS, ECS, Lambda, CloudFormation (10+ years)

● Containerization: Kubernetes, Docker, Helm, Argo CD, Rancher (6+ years)

● IaC & Automation: Terraform, Ansible, Chef, CloudFormation (8+ years)

● CI/CD: Jenkins, GitHub Actions, GitLab CI (7+ years) MLOps & Machine Learning Infrastructure

● ML Lifecycle: MLflow, SageMaker, Vertex AI, Kubeflow, TFX (3+ years)

● Orchestration: Airflow, Argo Workflows, Step Functions (2+ years)

● Feature Stores: Feast, Tecton, SageMaker Feature Store (3+ years)

● Model Tuning: Optuna, Ray Tune, Hyperopt, Grid/Bayesian Search (3+ years) Observability & Reliability

● Monitoring: DataDog, Prometheus, Grafana, New Relic (7+ years)

● Logging: ELK Stack, Fluentd, CloudWatch Logs (6+ years)

● Security: IAM, encryption, compliance, security auditing (10+ years)

● Programming: Python, Bash, PL/SQL (9+ years)

PROFESSIONAL EXPERIENCE

Boboa Consul (Consulting)

Staff Engineer - MLOps / Cloud Solution Architect

Jan 2021 – Present

Consulted for clients like PWC and Ellucian on projects that require domain expertise projects like PwC Insight and Ellucian HigherEds Cloud Migrations. Act as Staff Engineer and Cloud Solution Architect, leading the full lifecycle of scalable ML systems — from data ingestion and model experimentation to secure, production-grade deployment — across hybrid cloud environments (AWS, GCP, Azure). Architected and led development of Insight Platform, a distributed, multi-tenant MLOps system supporting data scientists and ML engineers with end-to-end capabilities for data ingestion, transformation, model training, batch/real-time prediction, and visualization. Operationalize intelligent workload orchestration across Spark, Hadoop, Hive, and BigQuery, routing jobs based on volume and runtime requirements; support GPU-accelerated training and serverless inference using EKS, AKS, and Lambda.

Implement robust CI/CD pipelines and infrastructure-as-code workflows using Terraform, Helm, and GitHub Actions to automate and secure the full ML deployment lifecycle — from feature pipelines to model APIs.

Design and productionize machine learning models for conversion rate optimization, SPV-based segment targeting, and email lead scoring / churn prediction — increasing engagement and retention across business units.

Conducted advanced EDA and statistical analysis to uncover behavioral signals and segment performance, using Pandas, Seaborn, and custom cohort logic to drive interpretable model design.

Led hyperparameter tuning and optimization for models including Logistic Regression, Decision Trees, XGBoost, LightGBM, leveraging GridSearch, Optuna, and Bayesian techniques to maximize performance across diverse use cases. Developed and maintained enterprise ML observability systems including model drift detection, feature health monitoring, performance dashboards (Superset, Prometheus, Grafana), and SLA-based alerting.

Regularly perform technical strategy reviews, approve deployment and optimization plans, lead production incident resolution, and provide hands-on troubleshooting and tuning for large-scale ML jobs.

Enable platform-wide security, tenant isolation, cost attribution, and access governance — empowering teams to innovate safely and independently within a shared infrastructure. Mentor engineers and data scientists across functions, reviewing code and architecture, coaching on modeling best practices, and evangelizing scalable, ethical ML system design. CAPITAL ONE

Data Infrastructure Architect

Jan 2014 – Mar 2024

Led critical data infrastructure initiatives for a Fortune 100 financial institution, architecting solutions that balanced security, performance, and reliability while processing billions of daily transactions.

Key Achievements:

● Enterprise Database Platform Architecture: Designed and implemented a unified database platform supporting 5,000+ databases across PostgreSQL, MySQL, Oracle, MongoDB, and Cassandra, reducing operational overhead by 65% while improving performance by 40%.

● Cloud Transformation Leadership: Spearheaded migration of 1,000+ applications and database systems to AWS cloud, implementing Infrastructure as Code (Terraform, CloudFormation) to reduce provisioning time from weeks to minutes while ensuring compliance with financial regulations.

● High-Availability Engineering: Architected multi-region, active-active database clusters with automatic failover capabilities, achieving 99.995% uptime for mission-critical systems and reducing recovery time objective (RTO) from hours to minutes.

● Data Infrastructure Automation: Developed a comprehensive self-service platform enabling development teams to provision, scale, and manage database resources through automated workflows, increasing developer productivity by 75% while ensuring governance and best practices.

● Database Migration: Led migration of 200+ databases to AWS RDS and EC2, implementing automated schema validation, data synchronization, and verification processes that ensured zero data loss and minimal downtime.

● Security & Compliance: Implemented data encryption, access controls, and audit mechanisms ensuring compliance with industry regulations while maintaining high-performance access patterns.

● Technical Leadership: Established Center of Excellence for Data Infrastructure, creating architectural patterns, operational playbooks, and training programs that improved engineering practices across 200+ developers..

● Containerization Strategy: Migrated monolithic data processing systems to microservices architecture on Azure Kubernetes Service (AKS), increasing deployment frequency from monthly to daily while reducing environment provisioning costs by 45%.

● Data Pipeline Optimization: Engineered high-throughput ETL pipelines handling 10TB+ daily data volume using event-driven architectures and streaming technologies, reducing processing latency from hours to minutes.

● Observability Implementation: Deployed comprehensive monitoring infrastructure using DataDog, Prometheus, and Grafana with custom dashboards and alerting, improving system visibility and reducing incident response time by 70%. EDUCATION & CREDENTIALS

Bachelor of Science, Marketing Information Systems University of Maryland University College (2011)

Professional Certifications:

● AWS Certified Solutions Architect Professional

● CKA Certification

● CompTIA Security+

● CompTIA Network+

STRATEGIC IMPACT

● Scale: Architected data systems processing 5+ billion transactions daily with sub-second response times

● Reliability: Engineered platforms achieving 99.995% availability in regulated financial environments

● Efficiency: Reduced infrastructure costs by $15M+ through optimization and automation

● Innovation: Pioneered cloud-native data architectures reducing time-to-market by 70%

● Knowledge Sharing: Mentored 50+ engineers in advanced data infrastructure practices References available upon request

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