William Tewalt
Sr. Director of Data & Analytics
Senior data and analytics leader with 10+ years of experience building production data infrastructure, ML systems, and AI-powered tools. Has led teams and initiatives spanning data engineering, data science, and full-stack software development across agency, startup, and enterprise environments. Builds things end-to-end: from Airflow pipelines and medallion architectures to recommendation systems, web apps, and LLM integrations. Currently targeting senior leadership roles in Data Engineering, Software Development, or DevOps.
Currently open to
- Sr. Director / VP of Data Engineering
- Sr. Director / VP of Software Development
- Head of Data / Chief Data Officer
- Principal Data Engineer
- Manage a team of experts across multiple data domains
- Architected medallion data infrastructure; established IaC, version control, and system-as-code as core data strategy pillars
- Built custom ML-driven recommendation system optimizing ~$4M in annual advertising spend via automated bid/budget management leading to a 20% increase in ROI
- Launched a secure web app with cloud identity provider integration to expose internal ML/AI tools
- Built PII-safe proprietary data processing tools and internal APIs powering internally hosted ML/AI applications
- Consolidated siloed data into unified performance dashboards
- Built and orchestrated automated data pipelines with Python and Apache Airflow
- Developed media attribution models guiding optimization of millions in annual ad spend
- Designed and maintained PostgreSQL database as foundation for company-wide analytics
- Established scalable development guidelines enabling efficient cross-team support
- Built internal and client-facing dashboards for data visualization and performance reporting
- Developed the statistical models core to operational efficiency and growth
- Analyzed census data in AWS Redshift to generate market expansion recommendations for C-suite
- Developed operational models used as the basis for platform gamification
- Built interactive geospatial visualizations for identifying market hotspots
- Designed company-wide dashboards delivering cross-functional performance insights
- Built models used for forecasting and risk scoring/clustering
- Identified instances of double-billing resulting in a recovery of over $500k
- Applied statistical methods, simulation, and data mining techniques to complex business questions
- Designed staffing projection and service delivery estimation methodology
- Automated interactive reports and dashboards supporting contact center operations
Self-hosted recommendation system automating bid and budget management across ~$4M annual ad spend; increased client ROAS by 20%.
Apache Airflow orchestration. Data from dozens of sources (CRMs, ad platforms, SFTP, APIs). Custom Python packaging and cloud infra.
Medallion architecture across AWS Redshift, PostgreSQL, and BigQuery; implemented SQLMesh org-wide for data lineage and isolated dev/prod environments.
Full-stack app in Django + React for hosting internal data science tools; integrated with internal and external APIs.
MCP-based tool enabling Claude AI to directly query and interact with internal database tables.
LLM-driven generation of search ad copy using dynamic performance data; custom web UI with user-defined theme inputs.
Geospatial + Google Places API tool tracking business rankings across city subsections over time; cloud object storage for pipeline I/O.
Python package published on PyPI. View on PyPI →