Senior Software Engineer · Noteefy

Nick Anderson

I'm the golfer who got the Landmand tee time off a Noteefy alert, and the operator trying to keep his own tee sheet full. I'd like to build the thing that does both.

15 years in engineering and data leadership. Today an owner-operator of an indoor golf facility and an AI-native builder shipping golf software.

  • I'm your customer.

    Owner-operator of Back Nine Golf Ankeny since February 2025 — indoor golf, 24/7 member access, three bays today and a fourth arriving.

    Tee-sheet utilization, no-shows, membership funnel and revenue per bay are numbers I run weekly and have already built software against.

    The facility runs on a few hours a week, and I'm hiring someone to take even that.

    The Back Nine builds — Owner Portal and Pulse Board

  • I'm your customer's customer.

    Noteefy is how I got on at Landmand.

    The Landmand story

  • I build the way you build.

    The job description asks for engineers who use AI coding tools to work efficiently.

    Every project on this page was built that way, over a year, with the commit history to show for it.

    How I work

Why I'm your customer's customer

The Landmand round

I didn't get a tee time during the Landmand-famous rush for 2025 tee times, so I was surprised and beyond excited when I got the Noteefy notification for an open tee time later that week.

I jumped on it, got it, and played one of the most enjoyable rounds of golf of my life.

For a kid who grew up playing golf in the middle of cornfields in Illinois, Landmand is the Field of Dreams.

That's the product working, from the other side of it — and it's why I want to build the next version.

I didn't take a picture at Landmand. I was busy. The hat at the top of this page is that hat, a few months later.

Stack fit

Your stack, item by item

This is Noteefy's published stack with my honest position on every piece of it, including the parts I would be learning. Nothing is rounded up: where I claim strength the work that proves it is linked, and where the experience is adjacent it says what actually transfers and what does not.

Strong 5 items

Shipped in production, repeatedly, with work on this page that proves it.

Adjacent 8 items

Not this exact tool, but the same problem solved with a different one. The concepts port; the surface is new. Weeks, not months.

  • Material UI

    Adjacent

    A tool-level swap for component libraries he has used with different tools — the componentization and theming habits carry over.

  • FastAPI

    Adjacent

    Python he has; the framework is a week. Pydantic overlaps with the schema validation habit he already uses.

  • MongoDB

    Adjacent

    Hasn't run Mongo at scale. Document modeling, access-pattern-first design, and denormalization tradeoffs are the same muscles as the DynamoDB single-table design he has shipped. Weeks, not months.

  • Snowflake

    Adjacent

    Years of the analytics-warehouse problem from the Athena/Glue/Redshift side.

  • Azure

    Adjacent

    AWS SA-certified and deep. Identity, networking, managed compute and CDN map concept-for-concept; the console, the IAM model and the CLI don't. Honest estimate of the ramp: weeks.

  • Redis

    Adjacent

    A tool-level swap for caching layers he's built with different tools.

  • Kubernetes

    Adjacent

    A tool-level swap for orchestration he's done with different tools.

  • Cypress

    Adjacent

    A tool-level swap for end-to-end testing he's done with different tools.

  • Ramp: Nothing in Noteefy's stack lands here: every item has at least adjacent experience behind it. The tier stays on the page because it is where an honest answer would go, and you should be able to see that it was offered.

Shipped work

A year of building, counted

Not a portfolio of screenshots. Every figure below was derived from the repositories themselves, and every one of them says what it counted.

  • 10

    Products built and shipped

  • 962

    Commits

  • 624

    Merged pull requests

  • 330

    Test files

  • ~161,000

    Lines of tracked code

  • 4,269

    CI runs

  • 5

    Live production sites

What each figure counted
Products built and shipped
Personal repositories under ~/bench with git history, excluding this application itself. One repository, one product.
Commits
Commits reachable from the default branch of each repository (git rev-list --count HEAD), summed.
Merged pull requests
Pull requests in the merged state, counted through the GitHub API per repository and summed.
Test files
Tracked files named as a test (*.test.*, *.spec.*, test_*.py, *_test.go) or living under a test, spec or e2e directory.
Lines of tracked code
Lines in git-tracked source files in the languages listed below — JSON seed data, Markdown, lockfiles, minified bundles and generated directories all excluded. Rounded down.
CI runs
Total GitHub Actions workflow runs per repository, read from the API total_count rather than a capped listing, so this is exact.
Live production sites
Repositories serving a public origin today. Deployment is not visible from git history, so the origins are listed in the script and the count is derived from that list.
  • 624 merged pull requests against 962 commits — almost every change went through a pull request with CI attached, on personal projects where nobody was making me do it.
  • 29 pipelines across 10 repositories, and 4,269 runs through them. Every project got CI, including the ones that took two days.
  • 330 test files under ~161,000 lines of tracked code. Tests are not something I add once a project gets serious.
  • 5 of them are serving a public origin today, all deployed the same way — AWS CDK through GitHub Actions over OIDC, no stored credentials.
  • Aug 2025 – Sep 2026 (14 months), alongside running the business full-time. Speed is the point; the tests and the pipelines are what make the speed safe rather than reckless.
  • 6 of 10 are golf. Not a pivot for this application — it is what I build.

Source files by language

  • TypeScript 78.6%
  • JavaScript 5.2%
  • Python 4.1%
  • HTML 4%
  • Other 8.2%

The products

All 10, one line each. These are personal projects — my own repositories, built on my own time.

  • School Bus Sports

    schoolbussports.com

    High-school schedules, scores, standings and rosters for two conferences, with recaps the Claude API writes strictly from the data that was collected.

  • ShotTally

    Golfshottally.com

    Golf calculators as a static site, generated by a zero-dependency Python build and served for about the cost of the hosted zone.

  • Swing Chopper

    Golfswing-chopper.nicholastanderson.com

    Upload a two-hour bay session and cut it into a highlight reel, with dual-stream capture from a Raspberry Pi at the simulator.

  • Men's All-City Draft HQ

    Golfmensallcity.nicholastanderson.com

    Fantasy-draft scouting for the Galesburg Men's All-City tournament — Tour-style player profiles built from newspaper and public archives.

  • Spoon River Advisory

    spoonriveradvisory.com

    The advisory practice landing page, on the same S3, CloudFront and CDK pattern every other site here uses.

  • Back Nine Owner Portal

    Golf

    One operations view for Back Nine Ankeny: camera and door access, per-bay projector control, tee-time no-shows, trash-can fill — four apps folded into one.

  • Back Nine Pulse Board

    Golf

    A kiosk Pulse Board a Raspberry Pi runs full-screen at the facility: membership pace, money, utilization and funnel, glanceable from across the room.

  • Golf Score Tracker

    Golf

    Round-by-round scoring with accounts and persistent history, built mobile-first for use on the course.

  • Take Me Somewhere

    Give it an origin city and your dates, get surprise destinations bundled with the flights and events that make them worth the trip.

  • AI Coloring Page

    A Raspberry Pi that listens for a spoken request, generates a coloring page from it and prints the thing.

Read it honestly

  • These are personal repositories. They are evidence of building habit, range and pace — not of shipping at team scale.
  • b9-ankeny-owner-portal, school-bus-sports and spoon-river-advisory have more merged pull requests than commits, so history was rewritten or every merge squashed. Commit counts understate those repositories; the pull request counts are sounder.
  • Derived from the repositories themselves by tools/stats/collect.mjs on 2026-09-12.

How I work

AI-native development, with receipts

Working with an agent well is a method, not a tool list. This is the method — and this page is the demonstration of it.

  • Plan before code

    The work is scoped into issues with acceptance criteria before anything is written. Every issue in this repository was written before a line of the site existed.

  • Parallel work in git worktrees

    Several threads run at once on isolated checkouts, so they never step on each other and each one lands as its own reviewable change.

  • CI is the judge

    Typecheck, lint, unit tests and end-to-end tests gate the merge. When a check goes red the agent fixes the code, not the check.

  • TDD, genuinely

    The failing test comes first. That is what makes code an agent generated safe to accept at speed — the test was written against the behaviour, not against the implementation that happened to appear.

  • Mock-first adapters

    Every integration ships fixtures next to its live adapter, so the repository runs with zero credentials — the Back Nine owner portal is built this way. It is what makes an agent useful on an integration-heavy codebase: it can run the thing.

  • Grounding over generation

    School Bus Sports uses the Claude API in production for game recaps, strictly grounded in the data that was collected. An editorial constraint in code, not a suggestion in a prompt.

  • 330

    Commits · School Bus Sports

    31 days of commit history. A live product for high-school sports coverage, with grounded AI recaps, taken from first commit to production.

  • 371

    Commits · Take Me Somewhere

    91 days of commit history. Sustained parallel delivery across worktrees, every change gated by CI before it merged.

  • 13

    Test files · Swing Chopper

    39 days of commit history. Regression tests that regenerate their own screenshots, so a visual change has to be accepted rather than quietly missed.

This page was built the way it describes. Every issue it was cut into, the agent lane each one was routed to, the pull request it landed as and the session behind it are published — rendered on this site, because the repository is private. Read how this page was built

Resume

Fifteen years, in order

The whole résumé is here — nine roles, the competencies behind them, and the credentials. Nothing is behind a download.

  1. Feb 2025 – Present

    Owner & Operator

    Back Nine · Ankeny, Iowa

    • Owner & operator of the first Back Nine location in Iowa.
    • Creating a 5-star customer experience by bringing an analytics and engineering mindset to operations — using data to drive decisions, evaluate outcomes, and continuously improve.
    • Exceeded all financial and customer benchmarking targets within the first three months of operation.

  2. Feb 2023 – Mar 2025

    Senior Data Engineer III, Product Data Management

    Principal Asset Management · Des Moines, Iowa

    • Led analytics and engineering strategy for Product Data Management; partnered with cross-functional stakeholders to align data and platform delivery with business objectives.
    • Mentored Lead, Senior, and Junior engineers on engineering best practices — reducing rework through outcome-focused user story development and engineering upskilling.
    • Coached Product and Delivery on best practices such as product definition, roadmapping, user story definition, effort estimation, and capacity planning.

    Concurrent secondary assignment, Feb 2024 – May 2024

    Senior Data Engineer III, Enterprise Engineering Experience

    Principal Financial Group · Des Moines, Iowa

    • Led a cross-BU initiative to develop the first reusable node modules for the enterprise GitHub CI/CD pipeline, improving deployment consistency and developer productivity at scale.
    • Contributed to the first enterprise-wide domain-driven design application pattern, laying the groundwork to standardize engineering practices across the organization.
    • Implemented new and established architecture patterns in Backstage, making it easier for all engineers to adopt enterprise best practices and stay up to date.

  3. Aug 2021 – Feb 2023

    Assistant Director – Engineering, Customer Marketing Intelligence

    Principal Asset Management · Des Moines, Iowa

    • Led design and delivery of Principal Asset Management's first scalable Machine Learning platform.
    • Drove full-cycle engineering delivery transformation: reduced time-to-delivery, mean time to resolution, and change failure rate while increasing deployment frequency — core DORA metrics.
    • Expanded available data sources 18x while simultaneously reducing engineering headcount 50%+ through strategic attrition.
    • Reduced engineer onboarding to under 1 day, enabling all 4 new engineers (including interns) to deploy to production within their first week.
    • Drove a department-wide cost optimization initiative, reducing AWS cloud spend by more than 50%.

  4. Oct 2020 – Aug 2021

    Senior Data Engineer II, Customer Marketing Intelligence

    Principal Asset Management · Des Moines, Iowa

    • Managed a team of 5 engineers delivering data products on AWS using Athena, Glue, S3, Lambda, Python, and CDK (Infrastructure as Code).
    • Designed and led adoption of product-aligned engineering metrics that resulted in increased stakeholder alignment and engineer autonomy.
    • Reduced data validation runtimes by more than 99% while increasing accuracy — significantly improving data quality and availability for downstream consumers.

  5. Nov 2017 – Oct 2020

    Advanced Analytics Technical Lead – Enterprise Analytics Tools

    John Deere · Des Moines, Iowa

    • Partnered with data scientists, data engineers, and other data professionals to onboard new and existing workloads onto Databricks from a variety of source architectures.
    • Designed and led development of an automated license reclamation process built in Databricks that saved Deere $100k's annually by reclaiming unused tool licenses.
    • Collaborated with Databricks and RStudio (now Posit) on a POC to run Shiny Apps on Databricks clusters.
    • Led enterprise-wide implementation of RStudio Server Pro and RStudio Connect across all John Deere business units — increasing user adoption by over 100% each year.
    • Consulted data scientists on best practices for serving Machine Learning models and analytics content.
    • Facilitated workshops and Communities of Practice (CoP) to upskill more than 200 data professionals.
    • Spearheaded a comprehensive research effort on modern analytics & data science tooling which included products from over 70 vendors.
    • Managed, consolidated, and negotiated legacy SAS contracts which enabled Data Scientists to move decades-old SAS workloads to AWS.

  6. Feb 2017 – Nov 2017

    Data Scientist, Credit Risk Analytics

    John Deere Financial · Des Moines, Iowa

    • Designed and implemented production Machine Learning models driving $2B+ in automated credit decisions annually.
    • Increased auto-approval rates 12% through feature engineering with no increase in expected credit losses.
    • Monitored and maintained all North American Construction & Forestry predictive models in production, updating them to sustain performance in changing business conditions.

  7. May 2016 – Jan 2017

    Data Analytics Developer, Credit Risk Analytics

    John Deere Financial · Des Moines, Iowa

    • Sourced and evaluated new data sources for credit decisioning and pricing models; partnered with legal and compliance to ensure regulatory alignment.
    • Re-platformed the database and ETL supporting all credit decisioning, which reduced runtimes for month-end processes from days down to minutes.

  8. Nov 2010 – May 2016

    Various Roles in Software, Data & Analytics

    John Deere · Des Moines, Iowa

    • Progressive roles spanning software development, data engineering, and analytics across multiple business units.

Core competencies

  • DevOps Platform Engineering
  • Scalable CI/CD Pipeline Design
  • Developer Experience (DevEx)
  • DORA Metrics & Engineering Analytics
  • AWS (Certified Solutions Architect)
  • Infrastructure as Code (IaC / CDK)
  • Agile Delivery & Technical Roadmapping
  • Engineer & Data Scientist Enablement
  • Formal & Informal Leadership
  • Machine Learning in Production
  • Developer Portal (Backstage)
  • AI-Driven Development

Education

  • In progress

    M.S. Computer Science (Concentration: Machine Learning) — 70% Complete

    Georgia Institute of Technology · Atlanta, Georgia

  • May 2016

    M.B.A., Business Analytics — Capstone: Practical Business Applications of Blockchain

    Loras College · Dubuque, Iowa

  • May 2013

    B.A., Mathematics (Minor: Computer Science) — Senior Inquiry: Forecasting Using Exponential Smoothing

    Augustana College (IL) · Rock Island, Illinois

Certifications

  • Issued Oct 2018 · Expired Oct 2021

    AWS Certified Solutions Architect – Associate

    Amazon Web Services

The close

Why this role, written once, properly

This page is what I bring to the Scout conversation and hand to Noteefy: the long answer to "why this role", written out in full rather than compressed into a cover letter nobody reads.

I am going through Scout the way Noteefy asked — this sits alongside that process rather than around it, and nothing here needs booking.

Email mentanderson10@gmail.com

That address reaches me directly, and a reply comes back from me rather than an inbox.