Python or C++
Our Client is a diversified digital asset investment firm adhering to the highest institutional standards, bringing together synergistic businesses in Trading, Alpha Strategies, Asset Management, and Venture Capital.
- Collaborates closely with quantitative researchers to comprehend their data requirements, furnish technical solutions, and seamlessly incorporate data engineering procedures into quantitative strategies.
- Designs, creates, and optimizes robust data pipelines that empower ETL processes catering to quantitative research, analysis, alpha forecasting, and execution.
- Enforces rigorous data quality assurance protocols to guarantee the precision, dependability, and uniformity of data inputs and outputs.
- Assesses, chooses, and oversees the pertinent data engineering tools, technologies, and infrastructure, with a primary focus on scalability and automation.
- Cooperates with compliance and risk management teams to assure adherence to data privacy, security, and regulatory compliance standards.
- Proficiently communicates intricate technical concepts to non-technical stakeholders, allowing them to comprehend the value and consequences of specific data engineering endeavors.
Skillset and Qualifications:
- Possesses over 3 years of experience in the field of data engineering, with a strong preference for prior involvement in a quantitative hedge fund.
- Holds a Master's or Ph.D. in Computer Science, Engineering, Data Science, or a related discipline.
- Demonstrates proficiency in programming languages like Python and C++, coupled with a track record in big data technologies. Displays robust knowledge of SQL and relational databases.
- Showcases expertise in the formulation and enhancement of data pipelines, data modeling, ETL processes, data warehousing, and data governance.
- Evidences the ability to effectively collaborate with quantitative researchers and various stakeholders, translating their demands into technical resolutions.
- Exhibits formidable analytical and problem-solving abilities, proficient in scrutinizing intricate datasets, recognizing patterns, and deriving significant insights.
- Thrives in a fast-paced and dynamic setting, capable of adapting to shifting priorities and emerging technologies.
- Possesses adept verbal and written communication skills.