• Lead a team of two across Data Engineering, BI, and Data Science.
• Stood up the Snowflake + dbt production stack from scratch, replacing direct queries against the production application database. Reduced analytical query times from hours to minutes and eliminated query-induced application slowdowns.
• Built and maintained 20+ greenfield Singer-based integration pipelines in Python, standardizing ingestion of external Point-of-Sale data and directly enabling customer onboarding and revenue growth.
• Implemented dbt pipeline powering primary application reporting; established team standards for testing, documentation, modularity, and lineage.
• Petitioned for and implemented Datafold for automated data validation across dbt pipelines.
• Built observability layer across 400+ ETL pipelines where none existed. Shifted from reactive customer complaints to proactive detection and resolution of pipeline failures.
• Developed reusable Bash CLI tooling that decomposed opaque Singer ETL flows into discrete Extract, Transform, and Load steps with interstitial files and summary statistics. Reduced debugging from days to hours, and to minutes when paired with AI agents.
• Drove roadmap planning and prioritization of integration projects in partnership with Sales to maximize revenue impact.
• Set documentation standards adopted across engineering teams.
• Received Cinch's Game Changer Award (Q2 2025) for company-wide impact.

• Led a team of four Data Engineers owning dbt and Snowflake implementation and governance.
• Cleaned up dozens of duplicative and contradictory dbt models. Reduced Snowflake compute costs, stabilized reporting, and restored stakeholder confidence in the data.
• Petitioned for budget and onboarded Datafold for automated data validation, replacing manual spot-checking and catching breaking changes before they reached production.
• Established PR review, testing, and scoping processes that reduced regressions and re-work.
• Enabled Sales and Marketing teams to identify and prioritize leads; built data pipelines supporting Payroll commission calculations.
• Recruited to Cinch during this tenure based on demonstrated impact.

• Led a globally distributed team of eight (Data Engineers, BI Engineers, and Analysts) across four countries, including direct reports and contractors.
• Owned customer-facing MicroStrategy BI offerings serving thousands of enterprise customers including Home Depot, T-Mobile, and Lowe's.
• Built tooling to trace and debug undocumented legacy ETL packages contributed by dozens of developers over years. Enabled rapid root-cause analysis when enterprise customer reports broke, often with no context beyond a forwarded email.
• Led dbt and Snowflake data warehouse buildout, contributing models to the platform team's shared dbt project.
• Delivered time-sensitive ad hoc data analysis for the Executive Leadership Team.
• Advocated for and secured promotions for direct reports across multiple review cycles.
• Reverse engineered code from other teams to diagnose and resolve a sudden spike in database CPU utilization.

• Maintained server infrastructure for custom reporting offerings.
• Resolved tickets related to breakages, and tracked to resolution.
• Provided mentorship and technical assistance to analysts and engineers within the team.
• Shared best practices / techniques to resolve technical issues.
• Created training materials and documentation.
• Performed code reviews and provided feedback.
• Acted as designated Team Leader when the team's Director was on extended leave.
• Led project to implement Observability across service backend.

• Built predictive model to detect and forecast data center hot-spots across a globally distributed SaaS security platform serving millions of users. Enabled proactive server provisioning before capacity was exceeded, preventing outages.
• Created population forecasting algorithm with less than 2% variance between predicted and actual globally distributed user volumes.
• Designed and implemented a custom Python ETL framework (10+ packages) to extract and blend data from disparate databases and APIs, powering all capacity planning analysis and statistical inference.
• Built web-based dashboard (Flask + Plotly) exposing capacity insights to internal stakeholders, backed by a purpose-built database.
• Automated daily report delivery to stakeholders.

• Deployed new configurations and ETL packages to stage client data for Natural Language Processing (NLP).
• Designed, deployed, and automated solutions to support daily operations and Workforce Management initiatives.
• Created packages to extract and process data points from raw XML reports which were aggregated and published to browser-based operational dashboards.
• Designed and programmed processes to extract, sessionize, and join important web-visitor attributes between Hadoop and NLP tools.

• Designed custom data consumption processes to manage Pay for Performance operations and optimize revenue.
• Automated report delivery, validation, consumption, and storage of KPIs from multiple data sources.
• Performed complex analyses for program stakeholders, which included invoicing and revenue forecasting processes.
• Designed tool to parse and store session-level details from millions of raw XML files, yielding an SQL-friendly historical data source (Data Warehouse).

• Used advanced techniques and quantitative skills to analyze and interpret web analytics and contact center performance metrics.
• Made recommendations to campaign leaders based on quantitative analysis.
• Developed and distributed regular operational reports to internal and external clients.
• Worked with globally distributed contact center partners to monitor operational performance.

• Managed resolution of escalations and production-related issues.
• Wrote queries and developed reports.
• Performed QA on benefit enrollment system configurations before moving to production.
• Identified and documented best practices for new and existing procedures.

Python CLI for isolated Docker-based dev environments where AI coding agents run with full autonomy: no credentials exposed, no accidental pushes. Headless orchestration with structured messaging, safe rsync-based export, and code statistics. Built spec-first using Claude Code as the primary implementation agent, a working proof of the methodology.

Published on PyPI

Cross-platform JSON diff tool with intelligent normalization, path exploration, and log analysis for JSONL/Singer tap formats.

Multi-platform releases (macOS, Windows, Linux)

Integrates Markdown note-taking with Todoist task management. Auto-migrates tasks with Obsidian URI backlinks and deduplication.

7 stars on GitHub

Diffs two delimited files (CSV/TSV) based on composite keys with field-level comparison and JSON output.

Native Obsidian plugin translating the markdown_todoist concept into the TypeScript plugin ecosystem.

“I've had the pleasure of working with Adam both as a peer at Lendio and as my manager at Cinch, and he is one of the strongest data engineering leaders I've worked with.

Read more

“I would work with Adam anytime, anywhere, in a heartbeat.

Read more

“Working with Adam was one of the absolute highlights of my time at Cinch. He is not only exceptionally talented and deeply knowledgeable as a data engineer, but also one of the most humble, kind, and genuine people you will ever meet. He leads in the best way possible—through example. Adam is incredibly efficient, intentional, and detail-oriented in everything he does. He lets the quality of his work speak for itself, consistently adding value to the company and making it impossible not to learn and grow simply by being around him.

Read more