- Страна
- Сингапур
- Зарплата
- 189 500 ₽ – 252 700 ₽
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Research Associate, Data Engineer
Исключительная вакансия в одном из самых престижных хедж-фондов мира. Высокая зарплата, сильная команда и прямое влияние на инвестиционные решения делают эту роль очень привлекательной для амбициозных инженеров.
Сложность вакансии
Высокая сложность обусловлена специфической культурой Bridgewater (радикальная прозрачность) и необходимостью глубокого понимания финансовых данных APAC региона. Требуется не просто технический навык, но и способность проводить статистический анализ качества данных.
Анализ зарплаты
Предлагаемая зарплата (189k-253k SGD) находится на верхнем уровне рынка Сингапура для специалистов с опытом 1-5 лет, значительно превышая средние показатели для обычных технологических компаний.
Сопроводительное письмо
I am writing to express my strong interest in the Research Associate, Data Engineer position within the Asia Strategies department at Bridgewater Associates. With a solid background in building robust data pipelines and a deep fascination with systematic macro strategies, I am drawn to Bridgewater’s unique culture of radical transparency and its commitment to understanding the fundamental laws of economics. My experience in managing complex datasets and ensuring data reproducibility aligns perfectly with your need for a hands-on engineer who can bridge the gap between raw data and actionable investment insights.
In my previous roles, I have specialized in transforming messy, high-dimensional data into research-ready assets, utilizing tools like Python, SQL, and Snowflake. I am particularly excited about the opportunity to own the end-to-end data lifecycle for the APAC pod, where I can apply my analytical skills to interrogate data distributions and structural breaks. I thrive in fast-paced environments that value intellectual curiosity and direct feedback, and I am eager to contribute to the evolution of your investment engine while growing alongside the industry’s most rigorous thinkers.
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Описание вакансии
About Bridgewater
Bridgewater Associates is a premier asset management firm, focused on delivering unique insight and partnership for the most sophisticated global institutional investors.
Our investment process is driven by a tireless pursuit to understand how the world’s markets and economies work — using cutting-edge technology to validate and execute on timeless and universal investment principles.
Founded in 1975, we are a community of independent thinkers who share a commitment to excellence. By fostering a culture of openness, transparency, and inclusion, we strive to unlock the most complex questions in investment strategy, management, and corporate culture.
Explore more information about Bridgewater on our website here.
Our Culture
Our culture is anchored in excellence, meaning constant improvement, and it is deeply tied to our mission. Because markets are objective, competitive, and getting smarter everyday, we need to keep rapidly improving to have any chance of beating them. Truth is our most essential tool for engaging with the markets and constantly improving because once you know what's true about your problems and opportunities, you can determine how to get better. Valuing truth means being transparent about your decision-making and mistakes, giving and receiving feedback with humility, and fighting for the best answers over hierarchy, ego, or self-interest. Operating this way is hard – it's only possible because we build meaning in our work and relationships. This meaning comes from the audacity of the mission, and the joy of working alongside people who make you a better version of yourself. The culture, like Bridgewater itself, is always evolving. In 1997 our founder Ray Dalio wrote down his lessons, starting with a Philosophy Statementwhich remains our foundation. This later evolved into a set of 300+ Principles. In 2022, when Ray transitioned the company, we re-underwrote several of those principles and evolved others, with a specific focus on Meritocracy. Today the culture sits, alongside our people, as our most important edge. When we get it right, it’s the engine that powers everything else.
About the Team
This role sits in our Asia Strategies department, whose goal is to continue our growth down the journey of being the premier investment management firm in Asia. This entails developing great investment strategies reflecting our expertise, generating alpha in the markets, researching and publishing our understanding of the macroeconomic environment, and designing solutions to help our clients invest across the region.
About Your Role
We are seeking a Data Engineer to join a PM-led pod focused on systematic macro and long/short equity strategies in APAC. This is a hands-on, embedded role working directly with the portfolio manager, quantitative researchers, and quantitative developers in a fast-paced investment environment.
Unlike centralized data platform roles, this position is deeply integrated with the investment process. You will own the end-to-end data lifecycle that powers alpha research, portfolio construction, and live trading – from sourcing and ingestion to profiling, validation, transformation, and delivery into research and production systems. You will collaborate with our quantitative researchers, developers and portfolio managers and have direct impact on the data and systems that drive investment decisions.
You will drive the following responsibilities:
- Identify and assess new datasets to identify their merit in our investment process.
- Build and maintain a catalog of datasets/vendors by attending data conferences, reading whitepapers, and taking introductory calls.
- Design, build, and maintain robust, scalable data pipelines supporting systematic macro and long/short equity strategies.
- Partner closely with researchers and quantitative developers to ensure data is research-ready, well-documented, and reproducible across simulation and live environments.
- Profile and interrogate datasets to understand distributions, coverage gaps, stability over time, and structural breaks.
- Implement data quality checks, anomaly detection, and monitoring to ensure accuracy, timeliness, and completeness of production datasets.
- Design and maintain our data ontology and schemas
- Work across a variety of datasets including traditional datasets (fundamentals, market data, security master, etc.) to large alternative datasets.
- Work with shared data engineering and platform teams to evolve the broader data ecosystem while maintaining pod-level ownership and agility.
- Contribute to improvements in tooling, standards, and best practices that increase research velocity and system reliability
- Work with the data vendors on data quality and new features that will benefit our investment process.
You will be a click for the role if you:
- Care deeply about building high-quality data that drives decision-making and directly impacts outcomes.
- Are motivated by owning critical datasets and pipelines end-to-end, and take pride in correctness, reliability, and durability.
- Enjoy working in real-world data environments where inputs are messy, definitions evolve, and good judgment matters.
- Are intellectually curious and enjoy interrogating data — understanding its structure, limitations, and behavior, not just moving it from point A to point B.
- Are proactive with a strong sense of urgency, desire to drive impact, and are comfortable working in a fast-paced environment
- Are relentless in their pursuit of learning and development
- Are non-hierarchical, willing to challenge the status quo, and seek to give and receive feedback openly (even when challenging)
- Are passionate about compounding understanding
- Are experimental with a drive to adopt new technologies and methods
Interested in learning more about working at Bridgewater? Hear about the experiences of our employees here.
Minimum Qualifications
- 1–5 years of experience as a Data Engineer or in a closely related role, either: embedded with systematic investment teams (hedge fund, asset manager, bank), or in a high-scale, data-intensive technology environment (e.g., consumer, payments, or platform companies).
- Strong programming skills in Python and SQL; experience building production-quality, maintainable data pipelines.
- Experience working with modern data platforms (e.g., Snowflake or similar cloud data warehouses).
- Familiarity with distributed processing and workflow orchestration (e.g., Spark, Airflow, or equivalents).
- Proven ability to reason about data correctness, lineage, versioning, and reproducibility in environments where data errors have material downstream impact.
- Comfort using lightweight statistical analysis and data science techniques to assess data quality, coverage, and suitability for research use.
- Demonstrated experience working with high-dimensional, messy, and evolving datasets, including financial market and reference data (e.g., prices, fundamentals, macro, corporate actions), or large-scale behavioral, transactional, or event-driven data with complex schemas and quality challenges.
- Experience working with datasets spanning multiple geographies, where data sources, standards, and availability vary materially by region. Familiarity with APAC data sets & providers a plus.
- Experience navigating APAC data realities, including jurisdiction-specific macro definitions, country-specific corporate structures, and uneven disclosure and historical coverage.
- Familiarity with differences between global and local data sources, including gaps between English-language and local-language
In addition, to succeed within our unique culture and work environment, individuals must demonstrate humility, innate curiosity, and openness to new ideas and approaches. Candidates must be driven, confident, and goal-oriented. All Bridgewater employees are expected to be honest, exceptionally direct, and eager to provide and receive objective feedback. Our employees constantly strive for self-improvement through feedback and self-reflection and are committed to the pursuit of excellence.
Physical Requirements
- The anticipated onsite requirement for this role is four days per week in our Singapore office.
Why Choose Bridgewater?
It takes all types to make Bridgewater great. We seek a diverse group of innovative thinkers and push them to engage in rigorous and thoughtful inquiry. We develop people through an honest examination of their abilities and performance, enabling personal growth and professional development. We strive to provide you with opportunities that will challenge you and unlock your potential.
Compensation Band
- The expected annual base salary for this position is SGD 189,500-SGD 252,700. The total compensation package includes variable compensation in the form of a discretionary target bonus.
One of our core priorities at Bridgewater is to enable our employees to build a great life and career, and we believe our benefits are an important extension of that philosophy. As such, currently Bridgewater offers a competitive suite of benefits. Explore more information about Bridgewater’s benefits on our website here.
Bridgewater reserves the right to change its current benefits program at any time, in a manner that is consistent with applicable federal and state regulations.
This job description is not a contract and confers no contractual rights, privileges, or benefits on any applicant or potential applicant. Bridgewater has the right to change any and all terms of this job description, including, but not limited to, job responsibilities, qualifications and benefits. Nothing in this job description constitutes an offer or guarantee of employment. Please note that wedoprovide immigration sponsorship for this position.
Bridgewater Associates, LP is an Equal Opportunity Employer
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Навыки
- Python
- SQL
- Snowflake
- Apache Spark
- Apache Airflow
- Data Pipelines
- Statistical Analysis
- Data Quality
- Financial Markets
Возможные вопросы на собеседовании
Bridgewater славится своей культурой. Этот вопрос проверяет готовность кандидата к прямой критике.
Расскажите о случае, когда вы получили жесткую критику своей работы. Как вы отреагировали и что изменили в своем подходе?
Роль предполагает работу с 'грязными' данными. Важно понять методологию проверки качества.
Как вы подходите к профилированию нового набора данных, чтобы выявить структурные сдвиги или аномалии до того, как они попадут в модель?
Проверка технических навыков в контексте масштабируемости.
Опишите архитектуру самого сложного конвейера данных (data pipeline), который вы разработали. С какими проблемами масштабируемости вы столкнулись?
Позиция требует понимания специфики азиатских рынков.
В чем, по-вашему, заключаются основные сложности при работе с макроэкономическими данными стран APAC по сравнению с западными рынками?
Проверка навыков взаимодействия с инвестиционной командой.
Как вы обеспечиваете воспроизводимость данных между средой симуляции (backtesting) и живой торговлей?
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- Страна
- Сингапур
- Зарплата
- 189 500 ₽ – 252 700 ₽