Data Engineer

Overview

• Develop and optimize advanced data platforms supporting investment strategies and analytics for a leading financial services firm.
• Collaborate with cross-functional teams to design and implement innovative data solutions and tools.
• Enhance data pipelines to ensure high performance, quality, and scalability across diverse datasets.
• Work with cutting-edge technologies to manage financial data storage and processing efficiently.
• Provide tailored data solutions to meet the dynamic needs of investment professionals.
• Ensure data integrity through robust validation, monitoring, and error-handling mechanisms.
• Investigate and resolve data issues to maintain seamless integration with external providers.
• Contribute to a collaborative environment with opportunities for professional growth and innovation.

Key Responsibilities & Duties

• Design and implement scalable data platforms to manage diverse financial datasets effectively.
• Develop automation tools to streamline data pipeline operations and improve efficiency.
• Collaborate with investment teams to understand and fulfill complex data requirements.
• Utilize timeseries databases for efficient data storage, querying, and analysis.
• Build and maintain data quality tools to ensure validation and error detection mechanisms.
• Investigate discrepancies in data and coordinate with providers for resolution.
• Integrate alternative and unstructured data sources into the existing data platform.
• Contribute to the development of innovative solutions to derive actionable investment insights.

Job Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• Minimum of 5 years of experience in software development and data engineering.
• Proficiency in Python and SQL for data manipulation and engineering tasks.
• Strong communication skills for effective collaboration across teams and stakeholders.
• Knowledge of financial products such as options and swaps is advantageous.
• Familiarity with AWS ecosystem and streaming pipeline technologies preferred.
• Experience with OLAP platforms and timeseries databases is beneficial.
• Understanding of key financial data vendors like Bloomberg and FactSet is a plus.