Adam Boscarino
AVP Data Engineering
Washington, District of Columbia, United States
Summary
🤩
Rockstar🎓
Top SchoolAdam Boscarino is an AVP of Data Engineering with 10+ years building and leading high-performing data platforms that power product and analytics teams. He has repeatedly architected cloud-native data stacks—driving Snowflake migrations, S3 data lakes, and Kubernetes-based Airflow deployments—to replace brittle cron and legacy ETL systems and improve reliability at scale. A hands-on leader, he mentors engineers in Terraform, Airflow, and production-grade tooling while shipping internal developer experience improvements that let data scientists deploy pipelines without needing infra expertise. His open-source contributions include enhancements to the widely used dag-factory Airflow utility, adding timezone-aware DAGs and better operator support, reflecting a pragmatic focus on developer productivity. Based in Washington, D.C., Adam combines deep operational experience with a cross-functional sensibility for translating end-user needs into dependable data products. He’s known for turning exploratory data processes into auditable, maintainable pipelines that accelerate business decisions.
10 years of coding experience
17 years of employment as a software developer
BS, Management Information Systems, BS, Management Information Systems at University of Vermont
Github Skills (6)
apache-airflow10
python10
pytest9
yaml9
packaging8
devops8
Programming languages (9)
Github contributions (5)
astronomer/dag-factory
Nov 2018 - Jan 2023
Dynamically generate Apache Airflow DAGs from YAML configuration files
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:33 reviews, 93 commits, 101 PRs in 4 years 2 months
Contributions summary:Adam primarily focused on enhancing the `dag-factory` project, which dynamically generates Apache Airflow DAGs. Their contributions involved dependency management with `pipenv`, adding testing tools like `pytest-cov`, and removing dependencies. They implemented timezone-aware DAGs and added support for PythonOperator. Furthermore, they also improved build processes, including removing pipenv and updating setup.py and the versioning.
pythonairflow-dagsapacheyaml-configurationconfiguration-files
ajbosco/reads
Sep 2018 - May 2020
Command line tool to interact with Goodreads
Contributions:2 releases, 21 commits, 17 PRs in 1 year 7 months
command-line-toolcommandline-toolinteractcommand-linecli
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