Opeyemi I.

Data Engineer

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Bio

Opeyemi I. is an accomplished Senior Data Engineer with over 7 years of experience architecting and delivering reliable, scalable data solutions across Azure, GCP, and Databricks platforms. Highly skilled in Python, SQL, PySpark, Bash, and experienced in leveraging Databricks, Delta Lake, dbt, Airflow, Azure Data Factory, and Fivetran for robust data engineering solutions, Opeyemi also brings hands-on expertise in Snowflake, BigQuery, and Looker for data warehousing and analytics. His strong DevOps proficiency includes…

  • Projects completed2
  • Hourly rate
  • 4+ years experience
  • Lagos, Nigeria
  • Member since Jun 2026
Industries
OtherDeep Tech & HardwareFinTechAdTech & MarTech
Expertise
PythonSQLPySparkBashTerraformGitKubernetesSnowflakeBigQueryAzureGCPApache Airflow
Video Intro
Assessments

General Project Assessment

Great on Implement LRU Cache Algorithm, Difficulty Medium · Great on Redesigning an ETL Pipeline for Enhanced Performance, Difficulty Medium · Great on Optimize Data Storage Strategies for Hybrid Cloud Environments, Difficulty Hard

Projects

Production-style Data Engineering Pipeline Built Using AWS, Snowflake, and dbt to Process Airbnb Data

This project demonstrates a production-style data engineering pipeline built using AWS, Snowflake, and dbt to process Airbnb data from raw ingestion to analytics-ready datasets.The pipeline is designed with scalability and maintainability in mind, leveraging a medallion architecture (Bronze - Silver - Gold) to progressively refine data for business use. Tech Stack Cloud Storage - AWS S3 Data Warehouse - Snowflake Transformation - dbt Language - Python 3.12, SQL Version Control - Git Key Features • Incremental Processing for scalable data pipelines • SCD Type 2 Snapshots for historical tracking • Modular dbt Models for maintainability • Reusable Macros for dynamic transformations • Data Quality Tests for reliability • Analytics-Ready Tables for reporting What This Project Demonstrates • End-to-end data pipeline design • Medallion architecture implementation • Incremental processing at scale • Historical tracking with SCD Type 2 • Production-style dbt structure • Strong data modeling practices More details can be found in the repo below https://github.com/Opsy-Daizy/dbt_snowflake_aws_project_end_to_end

Voice AI Impact Evaluation for Digital Service Access

This project evaluates how effectively a Voice AI channel supports digital service access, especially for users who may face accessibility barriers such as rural location, disability, or first-time digital use. The analysis uses a DuckDB SQL pipeline with a dbt-style layered model. Raw CSV files are loaded as source views, cleaned into staging views, aggregated into intermediate session-level metrics, and combined into an analysis-ready fact table: fact_voice_ai_sessions. The final model links voice session metadata, user attributes, AI performance metrics, turn-level error signals, and application outcomes. This enables evaluation of completion rates, drop-offs, AI friction, escalation behavior, and accessibility gaps across user segments and service channels. The project's main analytical goal is to identify where Voice AI improves access, where it underperforms compared with Web and USSD, and how high-severity AI degradation can be reduced by 40% while improving application completion. What the pipeline enables * Session-grain fact table with one row per voice session. * Integrates users, voice sessions, turns, AI metrics, and application outcomes. * Measures completion, drop-off, escalation, error severity, and accessibility segments. * Supports dashboard views for Voice vs Web/USSD comparisons and friction analysis. * Defines a practical 40% error-reduction target for high-severity Voice AI degradation. Technology: DuckDB SQL models with dbt-style source, staging, intermediate, and mart layers.

Experience

  1. Senior Data Engineer

    Insight2Profit· OtherAug 2025 — Present
    • Lead the design and building of modular, event driven data pipelines using Azure Databricks, ADF, and Delta Lake, improving processing performance by 50%.
    • Established quality controls (validation checks, schema enforcement, data tests) and integrated them into CI/CD workflows.
    • Partner with ML, Software Engineering, and Systems teams to streamline ingestion processes, reduce technical debt, and improve reliability.
    • Mentor junior engineers through code reviews and design discussions; help set practical engineering standards for delivery.
    • Oversee customer data governance, ensuring alignment with privacy standards and internal data usage policies.
    PythonPySparkSQLDatabricksDelta LakeAzure Data Factory (ADF)TerraformGitHub ActionsPubSubGitCI/CD

  2. Senior BI Engineer

    Wolters Kluwer· Deep Tech & HardwareAug 2022 — Aug 2025
    • Built and maintained over 40 ELT pipelines using Airflow, Snowflake, dbt, and Fivetran, reducing data latency by 25%.
    • Drove adoption of CI/CD practices, including automated model testing, environment deployments, and infrastructure provisioning.
    • Migrated legacy pipelines to cloud-native architectures, improving scalability and reducing maintenance overhead.
    • Developed analytical APIs and dashboards that improved sales and product performance reporting by 50%.
    • Collaborated with software and systems teams to streamline integrations and ensure stable data flows.
    AirflowSnowflakedbtFivetranPythonSQLTerraformLooker

  3. Data Analyst / BI Analyst

    Ecobank Nigeria· FinTechMar 2019 — Mar 2022
    • Built reusable ETL routines and automated recurring reporting workflows, contributing to improved profitability insights (20%).
    • Developed operational and executive dashboards in Power BI, including row-level security (RLS) to support compliance.
    • Led the shift from Excel-based reporting to automated BI solutions, reducing manual effort and improving accuracy.
    • Delivered forecasting and analytics using Azure ML and Cognitive Services to support planning and decision-making.
    SQLPower BIAzure MLMS ExcelData AnalysisDAX

  4. Google Analytics Consultant

    Digimedia· AdTech & MarTechJun 2018 — Mar 2019
    • Managed PPC analytics pipelines and reporting, improving digital ROI by 200% through better attribution and optimization.
    Google AnalyticsLooker
Education

  1. Bachelor of Technology in Biochemistry

    Federal University of Technology Akure (FUTA)Nigeria2011 — 2016
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