Data Engineer

Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation  for discovering unique market opportunities.

Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization.

Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.

At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do — combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best.

At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential.

Responsibilities

Being a subject matter expert, functionally and technically, to deliver security referential data needs for Tower’s global trading footprint

Analyzing production issues and implementing corrective measures to prevent them from recurring

Identifying various operational inefficiencies and developing automation efforts as part of the continuous improvement of the platform

Interacting with trading teams and users to handle issues

Strengthening and maintaining Tower’s security referential infrastructure to address trading and back-office needs

Taking end-to-end ownership: development, testing, release, and support

Qualifications

The ideal candidate will have:

A bachelor’s degree in computer science or a related field

2+ years of experience working in the financial trading industry

Rich experience working with security referential data for financial trading across a variety of asset classes - equities, derivatives, FX, fixed income, crypto

Brilliant problem-solving abilities

The ability to manage multiple tasks in a fast-paced environment

Proficiency in Python programming

Strong expertise in SQL databases

Familiarity working in an UNIX environment along with good shell scripting skills

Excellent written and verbal English communication skills

Benefits

Tower’s headquarters are in the historic Equitable Building, right in the heart of NYC’s Financial District and our impact is global, with over a dozen offices around the world.

At Tower, we believe work should be both challenging and enjoyable. That is why we foster a culture where smart, driven people thrive – without the egos. Our open concept workplace, casual dress code, and well-stocked kitchens reflect the value we place on a friendly, collaborative environment where everyone is respected, and great ideas win.

Our benefits include:

Generous paid time off policies

Savings plans and other financial wellness tools available in each region

Hybrid working opportunities

Free breakfast, lunch and snacks daily

In-office wellness experiences and reimbursement for select wellness expenses (e.g., gym, personal training and more)

Volunteer opportunities and charitable giving

Social events, happy hours, treats and celebrations throughout the year

Workshops and continuous learning opportunities

At Tower, you’ll find a collaborative and welcoming culture, a diverse team and a workplace that values both performance and enjoyment. No unnecessary hierarchy. No ego. Just great people doing great work – together.

Tower Research Capital is an equal opportunity employer.