Aspiring Data Engineer | Problem-Solver | Lifelong Learner
Based in Bradford, UK | LinkedIn • GitHub
After nearly a decade running a successful award-winning business, I’ve transitioned into the world of data and technology. I’m currently training as a Data Engineer with Northcoders, where I’ve been building robust data pipelines, working with cloud technologies, and applying Python, SQL, and ETL practices to real-world projects.
My background in aviation data and business leadership means I value accuracy, efficiency, and clear communication—qualities I now bring into my work as a aspiring Data Engineer.
Languages: Python • SQL • JavaScript
Data & Analysis: Pandas • NumPy • Matplotlib
Databases: PostgreSQL • MySQL
Frameworks & Tools: Flask • Django • React • Git • Docker
Cloud & DevOps: AWS (EC2, S3, Lambda, Step Functions, Cloudwatch) • Azure • Github Actions • Jenkins
An end-to-end ETL pipeline that extracts open environmental data, transforms it into clean, structured formats, and loads it into a PostgreSQL database. This project focuses on code readability, modular design, and real-world data handling.
Highlights:
- Developed a cloud ETL pipeline in Python (Polars, PyArrow) extracting OLTP data from AWS RDS, transforming to OLAP star schema, and storing Parquet in S3. Orchestrated with AWS Lambda, Step Functions, EventBridge, CloudWatch; managed via Terraform with CI/CD (GitHub Actions, Pytest, Black, Bandit) and Looker Studio analytics. Key Contributions:
- Overcame AWS Lambda Layer Limit by upskilling in Docker containerisation, enabling Lambda functions to run successfully with all required dependencies.
- Wrote production-ready Python code and automated tests for the data transformation Lambda function, ensuring accuracy and reliability.
- Designed and implemented a CI/CD pipeline with GitHub Actions, streamlining deployments and maintaining code quality.
- Played a central role in developing Terraform modules to provision AWS infrastructure, enforcing least-privilege IAM roles for secure and scalable deployments.
A serverless data privacy application that automates the obfuscation of sensitive fields across CSV, JSON, NDJSON, and Parquet files to ensure GDPR compliance. The solution is designed for flexibility, scalability, and reliability, supporting both CLI and API-driven use.
Highlights:
- Built a container-based AWS Lambda function deployed via API Gateway, enabling secure file processing from S3 source to destination buckets.
- Containerised the Lambda with Docker to overcome AWS layer limits and manage dependencies efficiently.
- Implemented Terraform for infrastructure-as-code and automated CI/CD pipelines for container build, push, and deployment workflows.
- Developed a Python CLI for local execution with AWS credentials, supporting both interactive and non-interactive modes.
- Achieved 100% test coverage using Pytest, ensuring robust obfuscation and error handling across all supported file types.
- Designed an API Gateway POST endpoint (/obfuscate) for seamless integration with external systems, delivering a fully serverless GDPR solution.
- Cloud-native pipeline deployment
- Data orchestration tools (e.g., Airflow, Prefect)
- Scalable storage and distributed systems
- I used to run West Yorkshire's “Best Indian Restaurant” (2022–2024).
- I’ve worked with aviation safety data and in team leadership roles.
- I'm passionate about clean code, data integrity, and continuous improvement.
- I hold a private pilot’s license and I love hiking challenges (UK & Yorkshire 3 Peaks ✅).
I’m actively looking for junior data engineering opportunities.
If you're working on something interesting or think I’d be a good fit for your team — feel free to reach out!