Why hire Jason
Plug-in technical leadership for modern data & AI systems
End-to-end builder
From business problem to production system: requirements,
architecture, implementation, and handoff. Comfortable owning
critical paths for data-intensive and AI-enabled projects.
AI + data, not AI or data
Combines deep data engineering and architecture experience with
active, daily work in LLMs, RAG, and AI-assisted development—
enabling practical, deployable AI instead of prototypes.
Enterprise-ready, startup-fast
Has shipped at Meta scale and as a founder. Understands
governance, reliability, and stakeholder management while moving
quickly and iterating in small, testable increments.
AI-powered development & automation
Modern data platforms & ETL/ELT
Cloud & serverless (AWS)
Graph & big data (Neo4j, Databricks)
Business intelligence & analytics
What I build
Concrete capabilities you can plug into your team immediately
AI-powered automation & agents
OpenAI · Anthropic · n8n
- Design and build workflows using LLMs (ChatGPT, Claude) for triage, document understanding, and decision support.
- Implement retrieval-augmented generation (RAG) with vector search and guardrails for reliability.
- Integrate AI into existing systems via APIs, queues, and serverless components.
Modern data platforms & pipelines
Airflow · Databricks · Spark
- Design ETL/ELT pipelines from transactional systems, APIs, and logs into analytic stores and warehouses.
- Standardize orchestration and monitoring for reliability and observability.
- Build analytics-ready models to feed BI tools and ML/AI workloads.
Cloud-native data & automation
AWS · Docker · Serverless
- Architect serverless systems using Lambda, S3, DynamoDB, SQS/SNS, and CDK.
- Build robust automation and integration services that interface with third-party platforms and internal tools.
- Use containers for browser automation and specialized compute workloads.
Analytics, BI & graph data
Neo4j · Power BI · Qlik
- Build graph-based models (Neo4j) to capture complex relationships and accelerate insights.
- Design BI solutions for executives and operations using Power BI, Tableau, QlikView/Qlik Sense.
- Connect production data models to clear, decision-ready visuals and dashboards.
Selected work
Examples of impact across enterprise and founder roles
Enterprise graph & Databricks platform
- Leading an organization-wide data modernization initiative, moving fragmented legacy systems into a Neo4j-based graph architecture.
- Architecting Databricks-powered ETL pipelines (Python, Spark, SQL) to unify data from Oracle, MongoDB, Elastic, PostgreSQL, and external APIs.
- Embedding AI tools into daily development workflows to accelerate delivery and improve code quality.
AI-powered automation agency
- Founded and operate a business process automation agency, delivering intelligent automation for operational workflows.
- Built AI-driven flows with n8n, OpenAI, and Anthropic APIs to augment decision-making and reduce manual work.
- Implemented AWS serverless solutions (Lambda, S3, DynamoDB) with Selenium-based web automation for external systems.
Mission-critical data pipelines at global scale
- Designed and implemented production data pipelines supporting Meta’s global operations.
- Delivered infrastructure and dashboards for safety coverage analysis across high-risk international markets.
- Used Airflow, Spark, and Presto in collaboration with data science and cross-functional teams to deliver high-visibility solutions.
Data platforms & BI leadership
- At Proofpoint, orchestrated data warehousing with MySQL, PostgreSQL, Python, and Airflow; delivered customer-facing BI dashboards and serverless monitoring on AWS.
- At ServiceLink, led business intelligence and analytics teams, built the core cost-of-goods-sold data warehouse, and delivered executive-facing reporting and automation.
Capabilities & tools
Technology stack that comes with the Jason Green “package”
AI & workflow tools
- ChatGPT, Claude, Cursor
- n8n, Replit
- OpenAI & Anthropic APIs
- LangChain, RAG workflows
Programming & data
- Python (10+ years), SQL (20+ years)
- R, Django
- Neo4j, MongoDB, Elastic
- SQL Server, MySQL, PostgreSQL, Oracle
Cloud & infrastructure
- AWS: Lambda, S3, DynamoDB, SES, SQS, SNS
- SAM, CDK, Serverless Framework
- Docker & containerized workloads
- Apache Airflow, Spark, Databricks, Presto
Analytics & BI
- Data warehousing & modeling
- Power BI, Tableau, QlikView/Sense
- Reporting & dashboarding for executives
- Statistical analysis & experimentation
Automation & integration
- Selenium & web automation
- API development & integration
- Microservices architecture
- Business process automation
Leadership & delivery
- Team leadership & mentoring
- Enterprise stakeholder management
- Product strategy & analytics alignment
- Consulting & advisory work
How to engage
Flexible ways to plug into your current roadmap
AI / data engineering role
Hire directly into your team to lead or strengthen AI, data
engineering, or platform initiatives—especially where AI and data
intersect.
Consulting & advisory
Short- to medium-term engagements to define architecture, create
implementation roadmaps, or stabilize/modernize existing data and
analytics environments.
Prototype & accelerate
Rapid prototyping of AI-backed workflows or data products to
validate ideas, de-risk investments, and create a clear path from
experiment to production.
Education & continuous learning
Formal training plus ongoing specialization in data & AI
Robert Morris University – Coraopolis, PA
Majors: Finance and Management · Minor: Computer Information Systems
Degree partially completed.
Johns Hopkins University / Coursera
Data Science Specialization (R programming focus)