Software engineer

Daniel Ackerman.

I work on payments, distributed systems, and performance.

Open to full-time engineering roles.

Engineering work

Selected
results.

These results come from prior engineering, advisory, and contracting roles.

RubyConf 2019 / Speaker

How do you make distributed systems fast and reliable under flaky network conditions?

My RubyConf talk on statistically optimal API timeouts.

Watch the talk

01 / Query optimization

3 days → 2 minper report

30+ collections. Thousands of field combinations.

A query optimizer that did only the work each report needed.

How it worked
  1. 01

    Define

    Reports crossed 30+ data collections and thousands of field combinations. Repeated database work and memory failures made them take up to three days.

  2. 02

    Build

    I built a query optimizer that chose only the steps each report needed.

  3. 03

    Check

    Reports finished in about two minutes. The result gave teams answers without a days-long wait.

02 / Infrastructure

~$15k / moinfrastructure costs removed

Predictive scaling. Zero-write tracking.

Two changes across different layers of the system cut the monthly bill.

How it worked
  1. 01

    Define

    Reduce the cost of running the platform by changing how it used servers and stored data.

  2. 02

    Build

    I built predictive scaling to match servers to demand, plus a link-tracking system that skipped database writes.

  3. 03

    Check

    Together, the changes cut the infrastructure bill by about $15,000 a month.

03 / Feed performance

300 → 5database queries per request

Rebuilt the backend. Cut the waiting.

Feed p95 fell from 2s to 200ms through query design, indexing, and caching.

How it worked
  1. 01

    Define

    A single feed request triggered about 300 database queries. The product feed’s p95 response time reached two seconds.

  2. 02

    Build

    I rebuilt the backend, improved indexing, and added caching. The query count fell to five.

  3. 03

    Check

    The feed’s p95 response time fell to 200 milliseconds. Shoppers could browse a more responsive feed.

Areas of
experience.

Payments & commerce at scale

I build and improve systems where a failed request can mean a lost sale. I worked as a software engineer on a payments team moving over $1B a month. My timeout work helped prevent millions of failed payments.

Distributed systems

I build high-throughput distributed systems. My work includes a platform handling tens of millions of real-time events a day through a workflow engine.

Capacity planning, tenant limits, and high-throughput pipelines.

Data systems & business intelligence

I build the data systems a business runs on—from complex reporting engines to the pipelines leaders use to understand performance.

Experimentation & observability

I make complex product behavior visible. I uncovered conflicting experiments, then shipped a shared framework for experimentation and observability.

Real-time software & advanced media

I build real-time conferencing software and media-processing systems.

Applied AI & classifiers

I build and train in-house classifiers: AI models that sort documents, route work, or flag items for review.