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 FileExtractStageTransformWarehouseBI Layer
Core stackPythonPySparkSQLAirflowPostgreSQLDockerAWSGCPPower BI
A containerised on-premise data platform built for a multinational retail scenario. Five
Docker services (PostgreSQL, Spark, Airflow init/webserver/scheduler) brought up by one command. A PySpark
medallion pipeline (Bronze partitioned Parquet to Silver joined frame to a three-table dimensional Gold layer)
runs end-to-end in 3 minutes 11 seconds at stock scale. Airflow's parameterised DAG supports both scheduled
stock runs (analytical truth) and on-demand scaled tests (architecture validation), demonstrated processing
7.5M rows through the pipeline at 2x scale.
A cloud-native ELT pipeline built for a global sports analytics scenario, shipped on
real Google Cloud Platform infrastructure. Cloud Composer 2 orchestrates a 14-task DAG with parallel fan-out
and a Silver quality gate. Dataproc Serverless runs the PySpark medallion transformations without any cluster
to manage. Bronze raw NDJSON stays in a GCS lakehouse; Silver and Gold materialize as BigQuery external tables
with explicit SchemaField declarations replacing autodetect. Real production deployment: 11m 53s optimized
runtime, 84% reduction after debugging a Dataproc machine-type provisioning issue, real GCP spend within the
free trial.
A distributed ETL pipeline that processes 1 million synthetic banking transactions
through five disciplined stages (extract, explore, clean, transform, load) into a validated PostgreSQL star
schema. Deterministic SHA-256 surrogate keys, type-aware cleaning that flows DECIMAL through to the warehouse,
validation at every transform stage, and idempotent re-runs that never duplicate a row.
XTD Research Labs: Async Ingestion & PySpark Medallion Pipeline
UK Carbon Intensity API · aiohttp async · PySpark · PostgreSQL
A three-stage pipeline built for a UK grid decarbonization research scenario. Async
aiohttp pulls 1,095 days of regional carbon intensity from a live government API into a Bronze data lake, with
semaphore-bounded concurrency and exponential-backoff retry. PySpark explodes deeply nested JSON and pivots
fuel types across Silver and Gold layers. A two-stage dedup-merge lands the result in PostgreSQL with
composite-key idempotency. 8.7M intermediate rows down to 19,728 daily research metrics.
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.
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.
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
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 Q3 2026.
dbtBigQueryLooker Studio
03
Stack
Skills & tech stack
Production-proven tools I use daily, and working knowledge I'm actively building on.
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.
04
Experience
Work history
6+ years across data engineering, fintech product operations, and analytics, with
quantified impact from production systems.
Data & Analytics Experience
Jan 2026 – Present
Amdari Inc.
UK · Remote
Data Engineer Current
Optimised PostgreSQL database architecture through schema normalisation, table partitioning, and
query tuning, achieving a £10K quarterly cost reduction in AWS S3 storage
while enhancing query performance by 40%.
Developed and deployed interactive Power BI dashboards, reducing executive
decision-making time by 30% through access to reliable, high-quality insights.
Automated repetitive workflows using Apache Airflow DAGs and Python scripts,
eliminating 20+ hours of manual data processing per month and improving operational
throughput.
Conducted root cause analysis on data inconsistencies using SQL and Python (pandas),
reducing reporting errors by 25% and strengthening data validation processes.
Partnered with business and product teams to translate requirements into scalable data solutions,
boosting project delivery efficiency by 20%.
Enhanced cloud infrastructure reliability through Grafana and Jenkins-based performance
monitoring, minimising downtime and improving system uptime to 99.9%.
Integrated CI/CD pipelines using Docker, Jenkins, and GitHub Actions, ensuring
consistent deployment of ETL workflows and reducing release rollbacks by 50%.
Lead end-to-end project delivery, including strategic planning, budgeting, resource allocation,
implementation, and evaluation, achieving 95%+ on-time project completion.
Oversee daily operations across procurement, logistics, warehousing, and distribution, leveraging
data analytics to improve operational efficiency by 20–25%.
Design, implement, and optimise operational processes and systems using data insights, reducing costs by
10–15% while aligning with strategic objectives.
Monitor supplier and logistics performance through KPI tracking and dashboards,
negotiating contracts and driving 10–20% improvement in supplier performance metrics.
Implement data-driven reporting frameworks to track operational metrics, workflow efficiency, and risk
management, ensuring 100% audit readiness and regulatory compliance.
Serve as a key liaison for clients and stakeholders, using analytics to inform decision-making, optimise
service delivery, and strengthen business relationships.
Data AnalyticsKPI DashboardsProcess OptimisationProcurementLogisticsVendor Management
Jan 2025 – Jan 2026
Yawee Foods Limited
E-commerce · Ipswich / Colchester, England
Retail Assistant / E-commerce Support E-commerce
with data analytics contributions
Built batch data workflows in Python: ingested CSV exports from the e-commerce
platform, applied cleaning, validation and standardisation, and produced analysis-ready datasets for
reporting.
Produced analytics reports on daily transactions and stock levels, surfacing inventory
trends that informed restocking decisions and reduced over-stocking / under-stocking.
Analysed sales data to generate actionable insights on product performance, sales trends, and customer
buying behaviour, supporting marketing strategy and operational planning.
Investigated customer enquiries and complaints to detect recurring patterns, recommending process
improvements to enhance service quality and retention.
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
Feb 2022 – Oct 2022
NOMBA (Kudi)
Fintech · Nigeria
Customer Success Associate Fintech
Delivered personalised, multi-channel customer support, contributing to 90%+ CSAT
through clear communication and positive engagement.
Collaborated with internal stakeholders to resolve customer issues efficiently, reducing average
resolution time by 25% and improving service consistency.
Maintained strong product and policy knowledge, decreasing repeat inquiries by 20% and
improving first-contact accuracy.
Resolved 70-75% of cases at First Call Resolution (FCR), escalating complex issues to
backend teams and following through to closure within SLA.
Logged and documented customer interactions with 100% ticket accuracy, ensuring audit
readiness and smooth stakeholder handoffs.
Explained solutions in clear, simple terms, reducing follow-up contacts by 15%.
Customer SuccessFCRSLACSATTicket Management
Sep 2019 – Feb 2022
Access Bank PLC
Banking · Nigeria
Customer Care Officer / ATM Custodian Banking
Supported customers across the full customer lifecycle (onboarding, activation, usage, issue resolution,
retention) via digital-first channels, maintaining 90-95%+ CSAT and fast response times.
Onboarded customers onto mobile banking applications, guiding users through setup,
verification, and feature adoption to increase digital engagement and self-service usage.
Resolved issues across electronic channels, payments, cards, and ATM services, escalating complex cases
where required and following through to resolution within SLA.
Processed customer account requests and service changes, ensuring KYC / AML compliance,
data accuracy, and adherence to internal controls and regulatory requirements.
Monitored service availability including ATM uptime, proactively identifying issues and
collaborating with internal teams to minimise customer impact.
Operated in a high-volume fintech environment handling 50+ customer interactions daily
while maintaining quality and accuracy.
Recognised in the top 5 nationwide for service delivery.
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
05
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.
Every CV I send is tailored to the role you're hiring for, mapping my work directly to the stack and
responsibilities you need. Send me a quick email with the role title (or a link to the job description) and
I'll send back a matched version within 24 hours.
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.