Build production-grade data pipelines.

Data Engineer in the UK with an MSc in Data Science. I design and operate reliable ETL/ELT pipelines on AWS, focusing on analytics-ready data models, reprocessing safety, and data quality.

SQL

Python

ETL / ELT

Airflow

AWS

Availability

Open to Data Engineer / Analytics Engineer roles in the UK.

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Featured Data Engineering Projects

Production-Style ETL / ELT Platform

Raw → staging → curated layers • incremental loads • validation • Dockerised workflows

Outcome: analytics-ready datasets with deterministic reprocessing, schema consistency, and automated data quality checks.

Repo

SQL Analytics & Data Modelling

Fact & dimension models • cohort & funnel analysis • query optimisation

Outcome: consistent metric definitions and performant SQL powering reporting and decision-making.

Repo

Event-Based Data Pipeline

Event ingestion • idempotent consumers • near real-time processing

Outcome: reliable event processing with deduplication and clean downstream tables for analytics use cases.

Repo

Core Stack

SQL: data modelling, optimisation, window functions
Python: ETL pipelines, validation, automation
Orchestration: Apache Airflow (incremental & batch workflows)
Cloud: AWS (S3, Redshift, Athena)
Tooling: Git, Docker, Linux

How I Build Data Systems

Design pipelines assuming upstream data will fail.
Build idempotent workflows with safe reprocessing.
Enforce data quality before data reaches consumers.
Balance correctness, performance, and operational cost.

Contact

Interested in data engineering roles or collaborations? Reach out:

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