HMRC-CIP/Equal Experts

Working on secure/compliant real-time data ingestion and warehousing for a petabyte scale analytics platform. Based on AWS using s3/hudi, Scala/Spark, Apache Kafka, Scala/Python/Jupyter Notebooks, and for infrastructure Terraform, Packer, Docker (Linux and bash).

Data Pipelines Engineer

Elsewhen/Finecast

Building an AI assisted TV advertising distributions system. Working as part of a small ML team of Data Scientists prototyping then productionising a model (Tensor Flow) that can optimally match slots during ad-breaks with advertisments based on a number of factors. Hosted in GCP (Cloud Run, Cloud Tasks, Vertex AI, Big Query), data pipelines using a custom Python app (housed in Docker containers linked via Cloud Tasks) and the infrastructure auchestrated via Terraform.

MLOps Engineer

Allplants

Assisting the team to improve a skeleton implementation and grow a data engineering team.

Allplants Data Warehouse

John Lewis

Part of a team developing an in-house recommendations service, to replace 3rd parties. Provided infrastructure and CI/CD tools to improve observability, automation, and more efficient data pipelines. Working closely with Data Science and Software Engineering teams to train, assess, deploy and monitor ML models for the John Lewis website.

John Lewis Reccomendations

Awaze

design and build for a new data-warehouse, consolidating and harmonising data from across many subsidiary businesses across europe. Coaching internal team on data-engineering practices and DataOps. Using Python (DBT, Jinja), Terraform, Snowflake, Matillion, Airflow, Liquibase, SQL, AWS (CloudWatch, EC2, EBS, Lambda, SQS, IAM, Networking etc…), SodaSQL.

Expert, freelance Scala engineers