> Markdown version of [/jobs/ext/4282465-data-engineer](https://www.wearedevelopers.com/jobs/ext/4282465-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Teza Group LLC - **Location:** Austin, TX, United States - **Contract:** Internship / Graduate position - **Skills:** Java (Programming Language), Airflow, Amazon Web Services, Amazon S3, Apache HTTP Server, Big Data, Continuous Integration, Directed Acyclic Graph (Directed Graphs), Data Cleansing, Data Infrastructure, Data Stores, Github, Python (Programming Language), PostgreSQL, MongoDB, NoSQL, Operational Databases, Performance Tuning, Query Optimization, Standard Sql, SQL Databases, Data Streaming, Data Processing, Scripting, Cloud Platform System, Data Management, Slurm - **Published:** October 16, 2026 - **Apply:** https://www.careerbuilder.com/job-details/data-engineer-austin-tx--528ca9c4-bc6f-403d-92ba-5b408dda4187 ## About the Role * 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. ## Description About the roleTezas 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 day120 TB of processed, query-ready data in historical storageThousands of scheduled jobs: run by cron today, actively migrating to Apache AirflowAlternative data delivered directly into the real-time feeds of live trading strategiesThis 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.LocationAustin, TX / Yerevan, Armenia (in-office requirement)Key ResponsibilitiesWork 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. Thats 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 were building right nowA 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 StackPython and Java · Apache Airflow · Slurm · NATS · PostgreSQL · MongoDB · S3 · NFS · GitHub ActionsBasic RequirementsProficiency 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 haveFinancial 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.BenefitsHealth, visual and dental insuranceFlexible sick time policy