James Aley
Technical Lead at Orbital Witness
Welwyn Hatfield, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolJames Aley is a Technical Lead with 17 years of experience building reliable data-driven products across startups and big tech, currently leading engineering at Orbital Witness. He combines deep statistical training (Master’s and Graduate Certificate with distinction) with hands-on big data and full-stack engineering—ranging from mobile teams at Microsoft to cloud and ML systems. A pragmatic, evidence-based leader, he champions continuous experimentation and learning to drive product and team decisions. James is also an active open-source contributor to high-profile Databricks projects, having implemented Redshift and CSV data source enhancements for Apache Spark that improved parsing, serialization, and atomic writes. Colleagues describe him as an empathetic coach who balances technical depth with delivery at scale.
17 years of coding experience
14 years of employment as a software developer
Brentwood County High SchoolBSc, Computer Science, 1st Class, BSc, Computer Science, 1st Class at King's College London, U. of LondonGraduate Ceritificate, Statistics, Distinction, Graduate Ceritificate, Statistics, Distinction at Birkbeck, University of London
Github Skills (14)
csv-parsing10
aws-redshift10
scala10
apache-spark10
amazon-redshift10
avro10
csv-parse10
jdbc10
data-processing10
testing9
sql9
amazon-s37
s3-bucket7
aws-s37
Programming languages (7)
Github contributions (5)
databricks/spark-redshift
Jul 2015 - Jul 2015
Redshift data source for Apache Spark
Role in this project:
Back-end Developer
Back-end DeveloperContributions:49 commits, 1 PR, 39 comments in 12 days
Contributions summary:James primarily contributed to the development of a data source for Apache Spark, specifically focused on integrating with Redshift. Their work included implementing the DataSource API for read functionality via JDBC, which involved creating a RedshiftRelation class to handle connections and data retrieval. They also added support for writing data to Redshift using Avro serialization and implementing a staging table strategy for atomic updates. Furthermore, the user refactored and added parameters, and improved the handling of data type conversions.
data-sourcedatabricksredshiftspark-sqlapache
databricks/spark-csv
Jul 2015 - Jul 2015
CSV Data Source for Apache Spark 1.x
Role in this project:Back-end Developer
Back-end DeveloperContributions:7 commits, 1 PR, 7 comments in 9 days
Contributions summary:James primarily focused on enhancing the CSV data source functionality for Apache Spark. Their contributions centered around adding support for comment characters within CSV files, improving parsing capabilities. They modified core files to handle comment markers, ensuring correct parsing behavior. Additionally, the user implemented and tested the feature across both Scala code and test suites to ensure robustness and reliability.
data-sourcecsvcsv-readerparquetcsv-data
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.