Job Overview
The Research Systems Principal Engineer will work on high-priority projects within Research Systems, embedding into the project team on a sustained basis, e.g. for our back-testing platform and for our forecasting system. The person will be a thought leader for projects, drive technical innovation and help the teams design and build high-quality solutions. The expectation of the role is to be hands-on, both implementing features and capabilities, as well as mentoring and guiding other team members.
Responsibilities
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Provide strategic direction on architectural decisions and design. Anticipate upcoming challenges and proactively work on technical solutions to address
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Implement features and capabilities with a focus on value for the business, accelerating the overall delivery of the project and provide working solutions for challenging and key areas of platform
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Provide guidance to other team members on development tasks
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Conduct code reviews, enforce coding guidelines, contribute actively during pair programming sessions aimed at enhancing overall quality of delivered artifacts
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Lead and participate in deep architectural discussions to ensure solutions are designed for successful deployment, security, cost effectiveness and high availability
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Participate in building a data and HPC platform that can meet the scalability and processing needs of Research and Research Systems
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Assist the team in investigating potential improvements achieved by adopting new data technologies and frameworks
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Achieve high quality metrics through automated testing, robust operational tooling and reliable designs
Qualifications
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Bachelor’s degree in Computer Science, Computer Engineering or a related discipline; at least 10 years of prior experience, financial services exposure is a plus
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Proven record of delivering solutions that are used in a production environment at scale and with high uptime requirements
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Proven record of building high-performance cloud native solutions on public cloud (AWS preferred)
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Solid experience dealing with large-scale deployments with high degrees of parallelism
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Experience with container technologies like Docker, Kubernetes, Helm
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Experience working with data lakes, data warehousing, and/or database systems, including data frameworks like Trino, Spark, Pandas/Polars, Iceberg, etc
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Experience with distributed compute frameworks and orchestration tools like Dask, Slurm, AWS Batch, Airflow, Prefect, etc
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Ability to write elegant code, and comfortable with picking up new technologies independently
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Proficient in at least one major programming language (e.g. Python, Java, Scala) and comfortable working with SQL
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Self-motivated and self-directed, ability to translate technical direction into functional solutions
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Experience leading projects or teams is a plus
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Experience managing stakeholders and expectations
Arrowstreet Capital is a Boston-based systematic investment firm that manages global equity portfolios for institutional investors around the world.
Arrowstreet Capital is an equal opportunity employment firm. All qualified applicants will receive consideration for employment without regard to sex, race, color, religion, national origin, ancestry, gender identity, genetic information, age, sexual orientation, pregnancy, medical condition, disability, veteran or military status, marital status or any other characteristic protected by federal, state, or local law.
Arrowstreet Capital is committed to working with and providing reasonable accommodations for qualified individuals with disabilities and disabled veterans. If you need a reasonable accommodation for any part of the employment process due to a disability, contact us to discuss the nature of your request and contact information.
Top Skills
What We Do
Arrowstreet Capital is a Boston-based investment manager that provides global and international equity investment strategies and fund products to institutional investors such as pension plans, endowments, foundations, and registered/unregistered commingled investment funds.
We offer a select range of global equity investment strategies managed as long-only, alpha extension and long/short utilizing a broad range of instruments, including swaps and futures. Our investment process utilizes quantitative methods that focus on identifying and incorporating investment signals into our proprietary return, risk and transaction cost models. Our investment approach involves creating and investing in diversified equity portfolios. We utilize a structured investment process that attempts to add value relative to a client specific benchmark. This involves identifying opportunities across companies, sectors and countries by evaluating a diverse set of fundamental and market-based predictive factors. Portfolios are constructed through the use of a mean variance optimizer and proprietary risk and transaction cost models.
Arrowstreet Capital manages approximately $100 billion for over 200 client relationships in North America, the United Kingdom, Europe and the Asia-Pacific regions.