Lead Data Analyst (Financial Domain)
Role Overview:
We are looking to immediately hire a senior-level data professional with extensive experience in data analysis, financial systems, and team leadership. The ideal candidate will be responsible for owning and advancing our entire data stack, including pipelines, analytics, reporting, and decision-support systems. This is a critical leadership role for someone who thrives in high-pressure, high-frequency trading environments and can proactively drive data innovation.
Key Responsibilities:
- Lead the design, development, and maintenance of robust data infrastructure and analytics frameworks.
- Perform complex data analysis to support strategic trading and business decisions.
- Collaborate closely with product, engineering, and trading teams to align data strategy with business goals.
- Build and mentor a high-performance data team as the company scales.
- Take ownership of data governance, accuracy, and integrity across systems.
- Proactively identify opportunities for optimization, automation, and innovation within the data stack.
Requirements:
- 5+ years of hands-on experience in data analysis, data engineering, or quantitative analytics, ideally in the financial sector.
- Prior experience working with banks, hedge funds, trading firms, or high-frequency trading environments is a strong plus.
- Expert in SQL, Python, and at least one modern data visualization tool (e.g., Power BI, Tableau).
- Good to have knowledge of data modeling, ETL, and modern data pipeline tools (e.g., Airflow, dbt, Snowflake, etc.).
- Solid understanding of financial markets, trading systems, and real-time data.
- Excellent communication and leadership skills — capable of mentoring and managing a data team.
- Proactive, self-driven, and capable of taking complete ownership of data processes.
- Experience with APIs
Preferred Qualifications:
- Master’s in Data Science or related field.
- Experience with quantitative modeling, algorithmic trading, or machine learning preferably in finance domain.
- Familiarity with cloud platforms (AWS/GCP/Azure) and data security best practices.
