Posting record
Open 12+ days
- Teza Technologies' site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Teza Technologies, so its true age is longer.
Last checked Nov 3, 2026.
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Not stated: Pay, real vacancy, AI screening.
Why these three
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Skills mentioned
About the role
About the role
Teza's Data Platform team owns the data the firm trades on: every backtest, every live strategy, every portfolio decision starts with data we ingested, cleaned, stored, and served.
The scale, in plain numbers
- 1 PB of raw historical vendor data, growing by ~150 GB every day
- 120 TB of processed, query-ready data in historical storage
- Thousands of scheduled jobs: run by cron today, actively migrating to Apache Airflow
- Alternative data delivered directly into the real-time feeds of live trading strategies
This is a hands-on position on a small team of data engineers with growth potential. The firm is looking for outstanding technical skills, strong attention to detail, and a desire to architect and build data platforms.
Location
Austin, TX / Yerevan, Armenia (in-office requirement)
Key Responsibilities
- Work directly with Portfolio Managers and Quantitative Developers: turn their requirements into datasets and pipelines, and be the person who knows every nuance of the data they trade on.
- Design and onboard new data sources into our warehouse; improve the robustness, speed, and scalability of our systems; manage data entitlements.
- Build automated systems for data cleansing, anomaly detection, monitoring, and alerting, bad data must never reach a strategy.
- Evaluate new tools and technologies for organizing, querying, and streaming large datasets, and when nothing on the market fits, build it. That's how the bitemporal store happened.
- Support the production data warehouse the firm depends on.
- Develop and maintain vendor relationships aligned with our business objectives.
What we're building right now
- A bitemporal data store, designed and written in-house from scratch. Every dataset answers both " what did we know then ?" and " what do we know now? " , which is what lets researchers trust a backtest.
- A Python 3.14 migration of a large, long-lived codebase.
- Adoption of the latest Apache Airflow: writing DAGs for the thousands of jobs moving off cron.
- Pipelines for market data and alternative data: everything from exchange feeds to weather.
- Real-time delivery: alternative data flows straight into strategies' live feeds. Pipelines you build sit in the trading path.
- CI/CD for all of it, in GitHub Actions.
Our Stack
Python and Java · Apache Airflow · Slurm · NATS · PostgreSQL · MongoDB · S3 · NFS · GitHub Actions
Basic Requirements
- Proficiency in Python and Unix/Linux for data manipulation, scripting, and automation.
- Strong SQL, including query optimization and performance tuning, and familiarity with NoSQL.
- A solid grasp of data modeling: normalization and denormalization, and the judgment to know when each applies.
Nice to have
- Financial industry experience or internships.
- Java (part of our platform is written in it).
- Experience with on-premises data infrastructure.
- Familiarity with a cloud platform (AWS or GCP).
- Apache Airflow or similar workflow orchestration tools.
Benefits
- Health, visual and dental insurance
- Flexible sick time policy
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