Data Engineer role focusing on building reliable data pipelines and architectures. Collaborate to ensure high - quality data availability for analytics, BI, and AI initiatives.
About the role
- Senior Data Architect responsible for building data infrastructure at Trexquant, integrating diverse datasets for research and simulation applications. Collaborating with teams to enhance data accessibility and quality.
Responsibilities
- Architect and implement a unified data platform that integrates hundreds of vendor datasets, providing consistent, accessible, and high-quality data to simulators and researchers.**
- Design efficient storage and retrieval systems to support both large-scale historical backtesting and high-frequency research workflows.**
- Develop intuitive researcher interfaces and APIs that allow users to easily discover variables, explore metadata, and assemble data into standardized stocks × values matrices for rapid hypothesis testing.**
- Collaborate closely with quantitative researchers and simulation teams to understand their workflows, ensuring the data platform meets real-world analytical and performance needs.**
- Establish best practices for data modeling, normalization, versioning, and quality control across asset classes and data vendors.**
- Work with infrastructure and DevOps teams to optimize data pipelines, caching, and distributed storage for scalability and reliability.**
- Prototype and deploy internal data applications that enhance research productivity and data transparency.**
- Mentor and guide data engineers to maintain robust, maintainable, and well-documented data systems.**
Requirements
- 7+ years of experience in data architecture, quantitative research infrastructure, or large-scale data engineering in a financial or research-driven environment.**
- Proven experience designing and implementing scalable data storage solutions (e.g., columnar databases, time-series systems, object stores, or data lakes).**
- Strong proficiency in Python and familiarity with modern data stack technologies (e.g., Parquet, Arrow, Spark, SQL/NoSQL, distributed file systems).**
- Deep understanding of time-series and financial data modeling, including handling multiple vendors, instruments, and frequencies.**
- Experience building data interfaces, APIs, or tools that serve researchers, data scientists, or quantitative analysts.**
- Ability to translate research needs into efficient data schemas and access patterns.****
- Bachelor’s, Master’s, or Ph.D. in Computer Science, Engineering, Mathematics, or a related quantitative field.**
- Strong collaboration, communication, and documentation skills.**
- Familiarity with cloud-based architectures (e.g., AWS, GCP, Azure) and modern data governance practices is a plus.
Benefits
- Competitive salary plus bonus based on individual and company performance.**
- Collaborative, casual, and friendly work environment.**
- PPO health, dental, and vision insurance premiums fully covered for you and your dependents.**
- Pre-tax commuter benefits.**
- Weekly company meals.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Data Engineer facing challenges in diverse sectors at Smarthis. Implementing data integration solutions and applying machine learning models for optimization.
Senior Manager leading a team focused on scalable, reliable data products. Driving engineering excellence at Grainger with innovative technology solutions.
Data Engineer designing and managing data platforms using Snowflake for Grainger. Leading collaboration and mentorship while optimizing data workflows and infrastructure.
Data Architect for Invinity developing data management and analytics platform. Collaborating with cross - functional teams to provide reliable and efficient data systems.
Data Engineer building and enhancing a modern Data Lake architecture on AWS for game analytics and event tracking. Collaborating with multiple teams for data analysis and reporting.
Manager, Quality - Business Data Engineer responsible for managing RQA data governance and analytics. Collaborate with teams to enhance data solutions and drive technological advancements.
Data Engineer designing and implementing data foundations for automation and AI solutions at RHI Magnesita. Collaborating with technical experts and ensuring data quality with occasional project - based travel.
Data Warehouse Tech Lead leading GCP data projects at Derevo. Collaborating with internal teams to deliver high - quality data solutions in a hybrid role.
Senior Data Engineer transforming core business processes for Ørsted commodity trading. Developing data pipelines and working with a globally distributed team in IT and digital solutions.