Data Engineer

Postgres
UNITED STATES
September 18, 2026
Full Time
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Job Description

Company: Teza Technologies
Location: Austin, TX / Yerevan, Armenia
Workplace Type: On-site (In-office requirement)
Employment Type: Permanent

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. 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.

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.

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.

What You’ll Do / 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.

Requirements & Qualifications

  • 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.

Preferred / Bonus Qualifications

  • 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 & Perks

  • Health, visual and dental insurance
  • Flexible sick time policy

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