AWS Platform Engineer, Options Market Data

Unlok; Houston (TX); In loco; USD 130.000 - 190.000; Tempo pieno

Descrizione del lavoro

Unlok is seeking an AWS Platform Engineer to productionize Python-based quantitative finance models and build scalable cloud infrastructure behind an options analytics platform.

You will design and operate AWS infrastructure, containerize workloads, and deploy end-to-end data pipelines for options data, exposing results via APIs and ensuring reliable, scalable services.

Competenze

• Hands-on experience ingesting and processing OPRA options market data.
• Advanced AWS experience with EC2, S3, IAM, VPC, Linux and cloud networking.
• Strong Python, Docker, SQL/PostgreSQL, backend API, and deployment skills.
• Experience designing data ingestion/ETL pipelines, schemas, indexes, and scalable storage.
• Familiarity with CI/CD and infrastructure automation (Terraform or CloudFormation).
• Ability to translate analytics code into tested, production services.

Mansioni

• Design, deploy, and maintain AWS infrastructure for Python analytics applications; containerize workloads with Docker and operate them on EC2/ECS or suitable AWS services.
• Take a working model from the quantitative team, connect it to market data, deploy and monitor its computations on AWS, store outputs, and expose via API.
• Build automated pipelines to ingest, validate, and retain historical and live options market data (chains, trades, quotes, prices).
• Design and optimize storage and querying using PostgreSQL, S3, and analytical formats; ensure point-in-time data access.

Conoscenze

Python

Docker

SQL/PostgreSQL

APIs

CI/CD

Strumenti

AWS

Terraform

CloudFormation

Linux

EC2/S3

Descrizione del lavoro

We are seeking an AWS Platform Engineer to productionize Python-based quantitative finance models and build the cloud infrastructure behind an options analytics platform. Our quantitative team develops Python models and analytics for options pricing, volatility surfaces, Greeks, risk metrics, and trading indicators; you will turn those prototypes into reliable, scalable services on AWS.

The ideal candidate has strong experience with AWS infrastructure, data pipelines, database architecture, containerization, cloud storage and backend engineering. Experience with financial markets, options, or trading data is a plus but not required.

Key Responsibilities

• Design, deploy, and maintain AWS infrastructure for Python analytics applications; containerize workloads with Docker and operate them on EC2/ECS or suitable AWS services.
• Take a working model from the quantitative team, connect it to standardized historical or live market data, deploy and monitor its computations on AWS, store validated outputs, and make them available through a consistent API.
• Build automated pipelines to ingest, validate, and retain historical and live options market data, including option chains, trades, quotes, and underlying prices.
• Design and optimize storage and querying using PostgreSQL, S3, and appropriate analytical formats; ensure accurate point-in-time data access.

Required Qualifications

• Hands-on experience ingesting and processing OPRA options market data, either directly or through market-data vendors, including real-time quotes, trades, and historical tick data.
• Advanced hands-on experience with AWS (EC2, S3, IAM, VPC), Linux, and cloud networking.
• Strong Python, Docker, SQL/PostgreSQL, backend API, and application deployment skills.
• Experience designing data ingestion/ETL pipelines, schemas, indexes, and scalable storage systems.
• Familiarity with CI/CD and infrastructure automation (e.g., Terraform or CloudFormation).
• Ability to independently translate existing analytical code into tested, maintainable production services.

Preferred Qualifications

• Experience with options pricing and risk analytics, high-volume time-series workloads, distributed processing, or numerical/scientific Python applications.