Note: Company “Hybrid” work attendance policy: In-office work attendance required at the aforementioned office address for collaboration days based on each team’s requirement; telecommuting / working from home is permissible for remainder of the same month.Duties: Design and develop data engineering solutions for supporting thousands of different tradable instruments, including stocks, bonds, futures, contracts, commodities, etc. Handle multiple on-going support rotations to ensure continual availability of our data pipelines and datasets. Design the development of programs and processes to perform statistical/quantitative analysis on datasets to ensure completeness and integrity. Design, develop, and engineer new software to support data engineering. Test of new features in the QA (Quality Assurance) environment, and deployment to production. Meet and consult with users to determine project requirements. Coordinate and manage project-related work with researchers and others on the engineering and business teams - including project updates, deployment scheduling and planning and defect/post-mortem analysis. Recommend and review corrective actions (technology and/or process based) and other project related activities across the Data Engineering organization. Identify, analyze, and address computer software performance bottlenecks, participate in code analysis reviews.Minimum education and experience required: Master’s degree or equivalent in Computer Science, Computational Finance, or related field; OR Bachelor’s degree or equivalent in Computer Science, Computational Finance, or related field plus 2 years of experience in software engineering, or related experience. Skills required: Must have experience with at least one object-oriented programming language such as Java or C++. Must have experience with data structures, algorithms, and engineering quantitative computer systems including parallel computing, large-scale computations, and statistical computer simulations of complex systems. Must have experience with scripting in Python using NumPy, Pandas, and Matplotlib. Must have experience with building unit tests. Must have experience with developing on Unix and Linux. Must have experience with using development tools including Jupyter Notebook, Jenkins, GitLab and VIM. Must have experience with using Git to version-control code. Must have experience with Relational databases (SQL). Must have experience with performing data analytics using a variety of tools (Python, SQL, and NoSQL). Must have demonstrated financial knowledge on different tradable asset classes (equities and fixed income). Must have experience with collaborating with various peer teams and business partners to drive requirement gathering, design, and solutioning discussions. Must pass company’s required skills assessment. Employer will accept any amount of experience with the required skills.Rate of pay: The base pay for this role will be between $165,000 and $325,000 per year. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.

Minimum Salary: 165000 Maximum Salary: 325000 Salary Unit: Yearly