Alexander
Ivanov

Five years of enterprise automation, ETL pipelines, and secure API integrations. Currently at Freddie Mac.

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01 / ABOUT RA 04ʰ 12ᵐ · DEC +18° 07′

Enterprise automation, ETL pipelines, and a few things just for fun.

I'm a software engineer with 5 years of experience building enterprise automation, ETL pipelines, operational reporting, and secure API integrations in Python and Java. I'm currently at Freddie Mac, where I design automated data workflows across ServiceNow, Snowflake, and Elastic, implement OAuth 2.0 authorization flows, and manage credentials through HashiCorp Vault and CyberArk.

On the side I climb (V6 boulders, 5.12a sport — working on V7), shoot pool, and ship small projects when something annoys me enough. The site you're reading was one of those projects.

02 / RECENT WORK RA 07ʰ 45ᵐ · DEC −11° 22′ All on GitHub →

Four projects, and how each one actually works.

Pick one, then step through its flow — the constellation lights the path.

trading_bot Source → CASE STUDY

THE PROBLEM The rules of momentum trading are the easy part. The discipline is the hard part, and a bot that invents its own reasoning is just a faster way to lose money.

THE CALL I MADE Every threshold traces to a source — 51 numbered rules, and each weight in the conviction engine carries the quote it came from. Conviction sets position size; hard gates decide whether to trade at all. Paper mode loosens the gates to collect data, live mode enforces them.

IBKR gateways

Scanner

Pattern engine

Conviction

Orders + risk

STEP 1 / 6

ALSO BUILT Loading every public repo from GitHub…

SilentSupply Java backend experiment. Java → AchievementHunter Track gaming achievements automatically. Python → gpu-search-bot Stock alerts during the GPU drought. Python →

03 / STACK RA 12ʰ 03ᵐ · DEC +42° 51′

Things I've shipped with.

Click anything for the receipts.

Languages & APIs

Monitoring & Data

Platforms & Security

Python — where it shows up

Freddie Mac · SE II Built modular Python ETL pipelines around single-responsibility components for independent testing, reuse, and scheduled execution across enterprise data workflows.

Freddie Mac · SE II Set up Python/Linux email automation for server-to-client communications tied to enterprise workflow notifications.

trading_bot Event-driven async trading system — scanner, pattern detectors, conviction engine, and risk limits.

ProjectClimbers The whole app — session logging and move tracking.

04 / RESUME RA 18ʰ 36ᵐ · DEC +38° 47′

Read it four ways.

May 2024 – Present Freddie Mac Virginia

Software Engineer II

✦ Built modular Python ETL pipelines around single-responsibility components for independent testing, reuse, and scheduled execution across enterprise data workflows.

✦ Integrated ServiceNow, Snowflake, and Elastic APIs to automate data retrieval workflows that previously required manual coordination across multiple systems.

✦ Pulled server telemetry from Elastic via API to generate operational reports supporting monitoring, troubleshooting, and capacity planning.

✦ Implemented OAuth 2.0 authorization flows for secure internal and external API authentication across automation endpoints.

✦ Managed sensitive credentials through HashiCorp Vault and CyberArk, eliminating local secrets handling in Python and Linux automation scripts.

✦ Scheduled and sustained recurring jobs through AutoSys and ServiceNow-defined intervals; supported operational follow-through when automation failed.

✦ Set up Python/Linux email automation for server-to-client communications tied to enterprise workflow notifications.

Python ServiceNow Snowflake Elastic OAuth 2.0 Vault CyberArk AutoSys

EDUCATION B.S. in Computer Science University of Maryland, Baltimore County Baltimore, MD

career/main · 3 roles on main · 4 active branches · rooted at UMBC click a commit to expand