Data Engineer
- Work directly with Portfolio Managers and Quantitative Developers to translate business requirements into technical solutions; be a resource to explain dataset details and nuances.
- Expand our data warehouse by designing and adding new sources and functionality; improve robustness, speed and scalability of our systems; manage data entitlements
- Provide innovative data management, analytics and technology input to the team and management.
- Evaluate new tools and technologies suitable for organizing, querying and streaming large datasets.
- Design and build automated systems for data cleansing, anomaly detection, monitoring and alerting.
- Support our production data warehouse as required.
- Develop and maintain strong vendor relationships aligned with our business objectives.
- Proficiency in Python and Unix/Linux for data manipulation, scripting, and automation.
- Strong SQL knowledge and familiarity with NoSQL databases (ideally Postgres and MongoDB), including query optimization and performance tuning.
- Strong understanding of data modeling principles, including both normalization and denormalization techniques.
- Familiarity with cloud platforms, e.g. AWS or GCP
- Experience with Git version control, collaborative workflows (e.g., Github), and understanding of CI/CD best practices.
- Bachelor's degree in Computer Science, Data Science or related field.
- Financial industry internships are a plus.
- Experience with Java recommended.
- Experience with on-premises data infrastructure (e.g., Hadoop)
- Experience with Apache Airflow or similar workflow orchestration tools.
- An understanding of best practices for data modeling, including data normalization techniques.
- Master's degree in Computer Science, Data Science or related field.
- Health, visual and dental insurance
- Flexible sick time policy
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