We are seeking a highly skilled and experienced Data Engineer to join our team. The ideal candidate will be responsible for designing and implementing a robust data infrastructure and analytical toolset to support Balance Sheet management and optimization activities of the Capital Markets group. This role is ideal for someone passionate about leveraging data to drive high-impact business decisions.
Essential Duties:
Data Infrastructure Development:
Identify, design, and implement a robust infrastructure for efficient data processing.
Optimize the loading, cleaning, transformation, and storage of complex financial, funding, and transactional data from various sources.
Utilize SQL, Python, and Snowflake for data handling and management.
Improve existing data models of business intelligence tools, enhancing data accessibility and promoting data-driven decision-making across the Bank
Analytical Tools Development:
Build analytical tools to monitor existing balance sheet risks, including interest rate, funding, optionality and liquidity risks, as well as changes in those risks across market environments.
Utilize tools to provide actionable insights for optimal balance sheet management.
Skills:
Technical Expertise:
Advanced Proficiency in SQL and Python are essential. Proven track record of deploying and managing python codebase in a production setting.
Experience with Data Warehousing Solutions: Proven experience with Snowflake or similar platforms.
Data Visualization Tools: Proficiency in using tools like Plotly, QlikSense, Tableau for data visualization.
Working knowledge of a Git repository for version control and collaborative development
Data Engineering Skills:
Data Processing: Experience in handling, processing, and extracting value from large, disconnected datasets.
Data Pipeline Development: Skilled in designing and implementing data pipelines for efficient data flow.
Quantitative Skills:
Statistical and Mathematical Methods: Familiarity with PCA, linear regression, logistic regression, KNN algorithm, and Monte Carlo simulations.
Analytical Abilities:
Collaborative Skills:
Data Infrastructure Development:
Identify, design, and implement a robust infrastructure for efficient data processing.
Optimize the loading, cleaning, transformation, and storage of complex financial, funding, and transactional data from various sources.
Utilize SQL, Python, and Snowflake for data handling and management.
Improve existing data models of business intelligence tools, enhancing data accessibility and promoting data-driven decision-making across the Bank.
Analytical Tools Development:
Build analytical tools to monitor existing balance sheet risks, including interest rate, funding, optionality and liquidity risks, as well as changes in those risks across market environments.
Utilize tools to provide actionable insights for optimal balance sheet management.
Education:
Bachelor's degree in computer science, Data Science, Finance, Engineering, Financial Engineering, Quantitative Finance or related discipline required.
Post graduate degree preferred.
Salary: $145,000 - $165,000
Skills: