Ben Marengo
Head Of Data & AI Engineering
United Kingdom
Summary
👤
Senior🎓
Top SchoolBen Marengo is a Head of Data & AI Engineering with 11 years of experience designing and leading cloud-first data platforms and teams across high-scale environments. He combines hands-on engineering—deep expertise in GCP, Airflow, Dataflow, BigQuery and distributed ingestion—with strong leadership in strategy, CD practices, and GDPR-aware data design that has delivered measurable cost and privacy improvements. A pragmatic advocate for both object-oriented and functional programming, he focuses on observability and reliability in production distributed systems. He has contributed to Apache Airflow (improving BigQuery integrations and XCom behavior) and maintains an open-source Home Assistant integration, reflecting a commitment to both enterprise and consumer-facing projects. Based in the UK, he balances technical breadth with people leadership and a penchant for automating the home in his spare time.
11 years of coding experience
14 years of employment as a software developer
MPhys Physics, MPhys Physics at The University of Manchester
English, German
Stackoverflow
1,729reputation
1.8mreached
15answers
10questions
syntax
top-5%
Github Skills (26)
apache-airflow10
data-pipelines10
python10
data-engineering10
work-flow10
workflow-engine10
gcp10
etl10
orchestration10
orchestra10
data-pipeline10
bigquery9
google-cloud-dataflow9
syntax9
kubernetes-pods8
Programming languages (12)
Github contributions (5)
apache/airflow
Jul 2017 - Dec 2019
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:
Data Engineer
Data EngineerContributions:18 PRs, 26 comments in 2 years 4 months
Contributions summary:Ben primarily contributed to the development and improvement of the Apache Airflow platform, a data orchestration tool. Their work includes bug fixes for BigQuery related issues, enhancements to XCom functionality for operator outputs, and refactoring to ensure consistent use of the `do_xcom_push` flag across various operators. Further contributions were made to enable XCom support in the GKEPodOperator and use dynamic temporary locations in the Dataflow operator, indicating a focus on Google Cloud Platform integration and efficient data pipeline operations.
monitorpythonschedulerapacheprogrammatically
marengaz/rakomqtt
Mar 2020 - Apr 2021
Interpreter between rako bridge and home assistant's mqtt light platform
Contributions:5 releases, 6 commits, 4 PRs in 1 year
lightassistantbridgemqtthome-automation
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