Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Data Engineer
Austin · Yerevan · Austin, Texas, United States
Open 3 months, first seen by us 119 days ago- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
On-site — work setting source
Location type: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Engineering — team source
Department: Engineering
From the employer’s posting
What you’ll work on
Full postingTeza'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.
1 PB of raw historical vendor data, growing by ~150 GB every day
Design and onboard new data sources into the warehouse
Build automated data cleansing, anomaly detection, monitoring, and alerting
Write Apache Airflow DAGs to replace cron jobs
Support the production data warehouse
Turn portfolio manager and quant developer requirements into datasets and pipelines
From the employer’s posting
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.
1 PB of raw historical vendor data, growing by ~150 GB every day
Design and onboard new data sources into our warehouse
Build automated systems for data cleansing, anomaly detection, monitoring, and alerting
writing DAGs for the thousands of jobs moving off cron
Support the production data warehouse the firm depends on
turn their requirements into datasets and pipelines
What you’ll bring
All qualificationsCore experience
- Proficiency in Python and Unix/Linux for data manipulation and automation
- Strong SQL, including query optimization and performance tuning
- Solid grasp of data modeling, normalization and denormalization
- Familiarity with NoSQL databases
Qualification wording
Proficiency in Python and Unix/Linux for data manipulation, scripting, and automation
Strong SQL, including query optimization and performance tuning
A solid grasp of data modeling: normalization and denormalization, and the judgment to know when each applies
familiarity with NoSQL
Benefits in the posting
Full benefits wording- Health, visual and dental insurance
- Flexible sick time policy
From the employer’s posting.
Posting record
Report an errorOpen 3 monthsWe first saw this posting 119 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 8, 2026119 days ago
- Recorded sightings
- 50
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 119
Up longer than most. Similar jobs usually come down between day 6 and day 54.
From 10,805 similar postings that came down. Coming down is not always a hire.
Teza Technologies is hiring
1 open job
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Java
- Python
- SQL
- AWS
- GCP
- MongoDB
- NoSQL
- PostgreSQL
- S3
- Airflow
Where the posting names them
Our Stack Python and Java · Apache Airflow · Slurm · NATS · PostgreSQL · MongoDB · S3 · NFS · GitHub Actions Basic Requirements
- Financial industry experience or internships. - Java (part of our platform is written in it). - Experience with on-premises data infrastructure.
- 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.
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.
- 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.
- Experience with on-premises data infrastructure. - Familiarity with a cloud platform (AWS or GCP). - Apache Airflow or similar workflow orchestration tools.
- 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
- 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.
- Familiarity with a cloud platform (AWS or GCP). - Apache Airflow or similar workflow orchestration tools. Benefits
Your next step
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About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
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
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Austin, Texas, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.