Data Engineer

Open to full-time
Bio

Seyi K. is a data engineer with several years of experience in data engineering, AI development, and DevOps across various industries, including SaaS and EdTech. Seyi utilizes technologies such as Python, Kafka, Celery, Spark, and SQL to build scalable data pipelines, microservices, and backend systems. He is adept at implementing distributed processing pipelines and enhancing system observability through centralized logging and event tracing. At Koloxo Home, Seyi led the development of a production-grade AI SaaS platform, designing modular backend services for scalable asynchronous processing. His contributions at Software Freedom Conservancy involved modernizing Git's testing framework, reducing manual debugging time by 40% and improving test efficiency by 30%. Seyi holds a degree in Software Engineering from Holberton School and is pursuing further studies in Data Science at Stanford University. He is well-suited for roles that involve building and optimizing data-driven systems and infrastructure in innovative tech environments.

Expertise
KafkaPySparkSQLPythonBashKubernetesNumPyFlaskAnsibleTerraformJenkinsAWSSnowflake
Video Intro
Assessments
APPLICANT AVG · 53%SEYI · 93%0255075100TopASSESSMENT SCORE (0–100)

General Project Assessment

(93/100)
  • Great on Find Indices of Two Numbers That Add Up to TargetEasy
  • Great on Design an ETL Pipeline for Healthcare Data IntegrationHard
  • Great on Design a Secure Data Storage System on AWS S3Easy
Projects

Modernizing Git Unit Tests Using Clar

I modernized Git’s internal testing framework by writing thousands of lines of C code focused on improving reliability, maintainability, and correctness of core infrastructure. My contributions are documented across multiple commits.

Experience

  1. Backend AI Developer

    Koloxo Home· Enterprise & SaaSDec 2025 — Jun 2026
    • Led development of a production-grade AI SaaS platform spanning 10,000+ lines of backend, frontend, and infrastructure code across distributed services and workflow automation systems.
    • Designed and implemented 8+ modular backend services using Kafka and Celery for scalable asynchronous processing and event-driven workflows.
    • Engineered distributed processing pipelines handling concurrent jobs, retries, and cross-service coordination with strong fault-tolerance guarantees.
    • Improved observability through centralized logging, event tracing, and debugging workflows for faster production issue diagnosis.
    • Owned end-to-end delivery of core platform features across architecture, implementation, testing, deployment, and production hardening.
    KafkaCeleryPythonFastAPISQLData Modelling

  2. DevOps Engineer

    Xenara Inc· Enterprise & SaaSAug 2025 — Dec 2025
    • Performed cost optimization to cut AWS computer power cost by 30%.
    • Set up monitoring using Prometheus to maintain site operationality and reliability by 20%
    AWSPrometheusDockerLinuxYAMLShellTerraform

  3. Software Engineer

    Software Freedom Conservancy· Deep Tech & HardwareDec 2024 — Mar 2025
    • Revamped Git’s testing framework by implementing Clar, which reduced manual debugging time by 40% and significantly raised automation across the project.
    • Developed C-based test cases that cut execution time by 30%, enhancing overall test efficiency and allowing for quicker iterations.
    • Established test reliability through the implementation of structured assertions and better error handling, which successfully reduced false positives by 25% and increased confidence in test results.
    • Authored technical articles detailing the test migration steps, guiding 200+ contributors and helping them navigate the complexities of the framework effectively.
    GitClarC/C++LinuxSystem TestingUnit TestingGitHub/GitLab

  4. Software Data Engineer

    Stackwisr Limited· EdTechOct 2023 — Jan 2025
    • Developed scalable ETL pipelines, optimizing data transformation and supporting analytics for over 1 million records.
    • Automated report generation using SQL and Power BI, enabling the team to focus on strategic tasks by reducing manual effort.
    • Designed and implemented scalable data warehousing solutions that improved query performance by 60%, helping users access information faster and more efficiently.
    • Resolved database issues swiftly, reducing downtime by 30%, which ensured greater system reliability for all users.
    • Applied machine learning and AI techniques to detect fraudulent transactions, enhance credit risk assessment, and automate financial data analysis.
    SQLPower BISparkKafkaPandasPower AutomateSnowflakeAzure Data FactoryPySparkDatabricksApache Hbase

  5. Software Engineer Intern

    ALX Africa· EdTechFeb 2022 — Jul 2023
    • Configured and refined web servers, reducing application load times by 35% and improving deployment efficiency.
    • Automated key procedure using Bash, C, and Python, reducing manual intervention by 50% and improving system efficiency.
    • Boosted database performance, improving query execution speed by 40% through schema design, index management, and query optimization.
    BashPythonMySQLDjangoGit/GitHubC/C++LinuxShellYAMLPytest
Education

  1. Geography - GIS

    University of LagosLagos, Nigeria2016 — 2021

  2. Data Science - Machine Learning and AI for Precision Medicine

    Stanford UniversitySan Francisco, California, USA2025 — 2025

  3. Software Engineering

    Holberton SchoolSan Francisco, California, USA2022 — 2023
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