Data Engineer at Amdari Inc. · Suffolk, UK

Building data systems
analysts trust.

I used to be the person who had to explain why the dashboard was wrong.

Six years inside fintech and banking systems showed me what bad data costs. Now I build the pipelines that fix it: production ETL, star schema warehouses, and CI/CD-ready infrastructure.

Based in Suffolk, England · Remote or hybrid · UK-based roles

Source File Extract Stage Transform Warehouse BI Layer
Core stack Python PySpark SQL Airflow PostgreSQL AWS Power BI
Or email me directly
02
Projects

Selected projects

Three more case studies covering different architectural patterns: an end-to-end ETL warehouse on Brazilian e-commerce data, a layered three-schema analytics platform, and a live web scraping pipeline.

PayFlow: ETL & Warehouse

9 source CSVs · star schema · idempotent loads

A production-style ETL pipeline that ingests 9 raw Brazilian e-commerce CSVs, validates and cleans through a multi-layer pipeline, and loads a full star schema into PostgreSQL. Idempotent loads, structured logging, and a single-command orchestrator.

9 source CSVsStar schemaIdempotent
PythonpandasPostgreSQLSQLAlchemySQL
View case study

ChocoDelight Data Platform

Layered architecture · 3 schemas · feature engineering

An end-to-end ETL pipeline that turns a flat chocolate sales dataset into a structured PostgreSQL warehouse with raw, operational, and analytics schemas. Includes 10+ engineered features, a full dimensional model, FK validation, and a one-command orchestrator.

3 schema layers5 source CSVs4 dim + 1 fact
PythonpandasPostgreSQLSQLAlchemyKaggle CLI
View case study

AliExpress Laptop ETL

Live web scraping · Selenium · feature engineering

A production-style web scraping pipeline that scrapes 60 pages of AliExpress laptop listings, cleans and enriches the data with discount metrics and price bands, and appends only new records to PostgreSQL. Append-only loads, in-memory df passing, and a health check before scraping.

60 pages per run6 engineered featuresAppend-only loads
PythonSeleniumBeautifulSouppandasPostgreSQL
View case study
Currently building
Analytics engineering project with dbt + BigQuery on public transit data. Materialised models, tests at every layer, generated lineage docs, and a live Looker Studio dashboard. Targeting Q2 2026.
dbt BigQuery Looker Studio
03
Experience

Work history

6+ years across data engineering, fintech product operations, and analytics, with quantified impact from production systems.

Jan 2026 – Present
Amdari Inc.
UK · Remote
Data Engineer Current
  • Designed end-to-end pipelines using Python, SQL & Apache Airflow. Improved batch processing efficiency by 35%.
  • Optimised PostgreSQL via partitioning & query tuning. Achieved £10K quarterly cost reduction in AWS S3 and 40% query performance gain.
  • Automated workflows with Airflow DAGs, eliminating 20+ hours of manual processing per month.
  • Integrated CI/CD with Docker, Jenkins & GitHub Actions. Reduced release rollbacks by 50%.
  • Monitored cloud infrastructure with Grafana, maintaining 99.9% uptime.
  • Built Power BI dashboards cutting executive decision time by 30%.
PythonSQLAirflowPostgreSQLAWSPower BIDockerGitHub ActionsGrafana
Jan 2025 – Jan 2026
Yawee Foods Limited
E-commerce · Ipswich / Colchester, England
Retail Assistant / E-commerce Support E-commerce
  • Monitored daily transactions and stock levels. Created dashboards and reports to track inventory trends and optimise restocking decisions.
  • Analysed customer inquiries and complaints to identify patterns and inform process improvements.
  • Generated insights on product performance using sales data to support marketing and operational decision-making.
CRMData AnalysisDashboardsInventory Tracking
Oct 2022 – Dec 2024
NOMBA (Kudi)
Fintech · Nigeria
Product Operations Associate Fintech
  • Monitored real-time transaction data, reducing downtime and improving uptime to 80%+.
  • Conducted quantitative analysis using Tableau, Mixpanel & SQL to guide retention strategies.
  • Led cross-functional incident response with engineering, compliance & customer success teams.
  • Processed support tickets in Zoho CRM, generating trend reports to identify systemic issues.
SQLTableauMixpanelZoho CRM
Sep 2019 – Feb 2022
Access Bank PLC
Banking · Nigeria
Customer Care Officer / ATM Custodian Banking
  • Tracked CSAT metrics across full customer lifecycle, maintaining 90–95%+ satisfaction scores.
  • Analysed mobile banking adoption data to optimise digital engagement and self-service rates.
CRMData AnalysisCSAT / NPS
Apr 2019 – Sep 2019
Interswitch Group
Fintech · Nigeria
Financial Inclusion Partner Fintech
  • Onboarded 20+ agents in assigned territories, tracking KPIs to optimise market coverage.
  • Built weekly Power BI dashboards tracking agent activity and revenue for senior management.
  • Identified bottlenecks via operational audits, increasing productivity by 15–20%.
Power BIExcelKPI Tracking
By the numbers
Headline impact
£10K
Quarterly saved
AWS S3 cost reduction at Amdari Inc. through partitioning and query tuning. Achieved within the first quarter of joining.
6+
Years
Across data engineering, fintech product ops, and banking analytics.
5
Flagship Projects
Production-style pipelines, all open-source on GitHub.
99.9%
System Uptime
Production data infrastructure monitored with Grafana and Airflow.
Industries Data Engineering Fintech Banking E-commerce Retail Analytics Financial Inclusion
04
How I Think

Engineering principles

Every project on this site follows a small set of positions I have taken often enough that they feel less like opinions and more like defaults.

Seven principles I bring to every project.

These are not borrowed from blog posts. They are positions I have defended in pull requests, learned from incidents, and applied in production. Each one comes with the trade-off I accept by holding it.

Read all seven principles
  • 01Schema is the source of truth, not Python.
  • 02Idempotency is a contract, not a feature.
  • 03Write logs assuming you'll be debugging at 2am.
  • 04Validate before you load, not after.
  • 05Configuration belongs in environment variables, not code.
  • 06Modular ETL beats monolithic scripts, always.
  • 07Engineer features in the warehouse, not in dashboards.
05
Stack

Skills & tech stack

Production-proven tools I use daily, and working knowledge I'm actively building on.

Production-proven
Python SQL PostgreSQL Apache Airflow Apache Spark PySpark SQLAlchemy pandas Power BI AWS S3 Docker GitHub Actions Grafana Git Tableau MySQL Jenkins dotenv / config
Working knowledge
Amazon Redshift Google BigQuery GCP Azure Apache Kafka Hadoop dbt Agile / Scrum
On Airflow
I use TaskGroups for clarity over SubDAGs. SubDAGs share a scheduler slot and quietly cause backfill pain.
On PostgreSQL
My default for analytics warehouses up to ~100M rows. Past that I'd reach for Snowflake or BigQuery before adding complexity.
On Python
I treat type hints as documentation, not safety nets. They make the next engineer's job easier. The runtime doesn't care.
06
Certifications

Credentials

10Analytics
Data Engineering
Jan 2026
Udemy
Diploma in Web Development
Nov 2024
Product School
Product Analytics Micro-Certification
Jan 2023
Alison
Introduction to Tableau Desktop
Jul 2023
Google
Fundamentals of Digital Marketing
Jul 2020
FITC
Basic Banking Operations
Apr 2018
07
CV

Download my CV

Yomi Ismail: Data Engineer

Full work history, ETL projects, data warehousing and analytics engineering contributions.

Contact

Let's build
something together.

Currently looking for Data Engineer or Analytics Engineer roles. Also open to senior data platform or technically-focused operations positions with a strong data component. Available remote or hybrid across the UK. If you're hiring or have a project you'd like to discuss, feel free to get in touch.