Data Engineer

Location Zurich
Discipline: Financial Technology
Job type: Permanent
Contact name: Lewis Piper

Contact email:
Job ref: 1758
Published: 3 months ago

Data Engineer 
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.

Key Responsibilities:

  • 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.