Manage, evaluate, and enhance our existing finance-related data platforms, identifying opportunities to leverage emerging technologies and cloud-based solutions.
By modernizing our data infrastructure, we can improve scalability, accessibility, turnaround times, and security, paving the way for advanced analytics and driving data-based insights.
Contribute to the establishment of standards and procedures for data governance, integration, quality management, and lifecycle management.
By optimizing these processes, we will ensure data consistency, accuracy, and timeliness, enabling reliable decision-making across the organization.
Collaboration: Evaluate, enhance, and modernize the Firm’s data platforms, including exploring emerging technologies and cloud-based solutions to improve scalability, accessibility, and security.
Contribute to establishing and optimizing standardized procedures for data management, data governance, data integration, quality management, and lifecycle management to ensure data consistency, accuracy, and timeliness.
Collaborate with cross-functional teams, business units, and senior management to drive data-driven initiatives, foster a data-driven culture, and ensure alignment with organizational goals.
Monitor and optimize enterprise data platforms and data engineering processes, identify areas for improvement, and drive innovation to enhance data processing efficiency, data quality, and overall system performance.

Bachelor’s degree in Computer Science or a related field is preferred.
Five or more years of experience in a senior data engineering or database architecture role.
Industry-recognized database or cloud platform certifications are a plus.
Experience working with cloud-based data platforms and services, such as Snowflake or Microsoft Fabric.
Advanced SQL development and modeling skills, including associated tools.
Strong experience designing, building, and maintaining data integration and ETL/ELT pipelines to support creation of data warehouse and analytical data models.
Working knowledge of Python for data engineering and automation.
Proven experience with relational database management systems and related data technologies.
Experience integrating with APIs and working with structured and semi-structured data formats such as (e.g. JSON and XML).
Experience using Git or similar tools for source control and version management.
Experience working in an Agile development environment.
Experience with database performance monitoring and tuning.
Familiarity with AI and large language model technologies.
Ability to work independently and collaborate effectively in team environments
Excellent organizational, customer service, and problem-solving skills.

Senior Data Engineer

Key skills