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To solve data-intensive problems, you need serious data infrastructure. From standing up distributed data storage, to tuning parallel runtime engines, you can count on me to deliver.
I build the whole data engineering stack: Sourcing datasets, developing ETL pipelines, and delivering reliable production outputs.
If you have a treasure trove of valuable data, I can help you access it. From data warehouse (and data lake) development, through analytics application set-up and training, I can do it all.
If you store any user-data, you need a data governance system. By combining my legal background and technical know-how, I build systems that clean user data, provide audits, generate automated documentation, and are capable of self-validation.
Moving distributed systems to (or from) a cloud vendor is intensive work. Let me plan and execute the project for you, so you can get back to work.
If you have an engineering team that is new to big data, I can get them up to speed fast. My blog is a great example of my ability to teach these concepts.
I've spent a decade working with big data. I can help you get the results you need.
Learning to ingest, store, process, and operationalize big data can take years. I have first hand experience delivering quality applications in a range of businesses.
I spend my workdays helping businesses get to grips with their ‘big data’. That usually means architecting, building, deploying, and monitoring data pipelines using Spark, Kafka, Hadoop, and more.
I’m a father and husband, and would not be capable of doing anything useful without my super smart and supportive wife, Alexandra.
Prior to Rathbone Labs, I founded and ran a data analytics start-up (Beekeeper Data), ran a team as VP of Engineering at Kickbox, designed and built distributed software at Shoutlet (acquired by Spredfast), built large scale analytics infrastructure at Foursquare, and real-time analytics software at Drop.io (acquired by Facebook).