Data Engineer

The Data Engineer is responsible for empowering the Data team to achieve its primary objectives: ingesting, transforming, and exposing real-time, event-driven data streams related to the firm's data assets. The ideal candidate should demonstrate a passion for continuous improvement and a dedicated focus on enabling consumers to make data-driven decisions.

Responsibilities

• Prioritize and rapidly collect raw data from source systems, efficiently store it, and employ fast and reliable access patterns.
• Understand system protocols, operations, and data flows while staying aware of current and emerging technology tools like Python, Cloud Native, Azure, Databricks, Airflow, SQL, Containerization, and APIs. Independently develop a software stack, and comprehend building blocks, interactions, dependencies, and tools necessary for software and automation work. Independent study of evolving technology is expected.
• Drive engineering projects by developing software solutions, conducting tests and inspections, and building reports and calculations.
• Focus on innovation and enablement, contributing to designs that implement new ideas improving existing and new systems/processes/services. Review existing designs and processes to identify more efficient methods of completing work effectively.
• Maintain knowledge of existing technology documents, write documentation, and document system designs, presentations, and business requirements.
• Collaborate with technical teams, utilize system expertise to deliver technical solutions, and contribute to the development of others through mentoring and learning sessions.
• Drive team practices and procedures for repeatable success and defined service expectations.
• Play a collaborative role in long-term department planning, focusing on initiatives that empower data, enhance operational efficiency, and promote sustainability.
• Monitor and evaluate the overall strategic data infrastructure, track system efficiency and reliability, identify efficiency improvements and mitigate operational vulnerabilities.
  

Qualifications

• Bachelor's degree or relevant work experience in Computer Science, Mathematics, Electrical Engineering, or a related technical discipline.
• 3-5 years of experience developing software in a professional environment, preferably in financial services but not required.
• Strong problem-solving skills, capable of analyzing root causes and proposing solutions.
• Familiarity with API-based data distribution.
• 3 years of hands-on experience in Data-Driven Enterprise Application development, preferably in the financial industry.
• Understanding of Enterprise architecture patterns, Object-Oriented and service-oriented principles, design patterns, and industry best practices.
• Foundational knowledge of data structures, algorithms, and designing for performance.
• Proficiency in Python and familiarity with technologies such as Cloud Native, Azure, Databricks, Airflow, SQL, Containerization, and APIs.
• Experience in database technology like MSSQL and of key-value and document databases like MongoDB, DynamoDB, and Cassandra.
• Comfortable with core programming concepts and techniques.
• Excellent communication skills and the ability to work with subject matter experts to extract critical business concepts.
• Ability to work and potentially lead in an Agile methodology environment.