Overview

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 pertaining to the firm’s data assets. The ideal candidate will exhibit passion for continuous improvement and a dedicated focus on enabling consumers to achieve their goals by making data driven decisions.

Responsibilities

• Prioritizes and executes rapid raw data collection from source systems, targets and implements efficient storage of, employs fast and reliable access patterns.
• Understands system protocols, how systems operate and data flows. Aware of current and emerging technology tools and their benefits. Expected to independently develop a full software stack. Understands the building blocks, interactions, dependencies, and tools required to complete software and automation work. Independent study of evolving technology is expected.
• Drives engineering projects by developing software solutions; conducting tests and inspections; building reports and calculations.
• Strong focus on innovation and enablement, contributes to designs to implement new ideas which improve an existing and new system/process/service. Understands and can apply new industry perspectives to our existing business and data models. Reviews existing designs and processes to highlight more efficient ways to complete existing workload more effectively through industry perspectives.
• Maintains knowledge of existing technology documents. Writes basic documentation on how technology works using collaboration tools like Confluence. Creates clear documentation for new code and systems used. Documenting systems designs, presentations, and business requirements for consumption and consideration at the manager level.
• Collaborates with technical teams and utilizes system expertise to deliver technical solutions. Continuously learns and teaches others existing and new technologies. Contributes to the development of others through mentoring or in-house workshops and learning sessions.
• Drives team practices and procedures to achieve repeatable success and defined expectation of services
• Provides a significant collaborative role in long-term department planning, with focus on initiatives achieving data empowerment, operational efficiency and sustainability
• Monitors and evaluates overall strategic data infrastructure; tracks system efficiency and reliability; identifies and recommends efficiency improvements and mitigates operational vulnerabilities.

Qualifications

• Bachelor’s degree or relevant work experience in Computer Science, Mathematics, Electrical Engineering or related technical discipline.
• 3-5 years of experience developing software in a professional environment (preferably financial services but not required)
• Problem solving skills – able to work through a problem, analyze root cause and propose solution.
• Familiarity with API based data distribution.
• 2-3 years of hands on Data Driven Enterprise Application development, preferable in financial industry
• Understanding of Enterprise architecture patterns, Object Oriented & Service Oriented principles, design patterns, industry best practices
• Foundational knowledge of data structures, algorithms, and designing for performance.
• Proficiency in programming in Python and familiarity with Java, C#; willingness to learn and adopt new languages as necessary
• Experience in database technology like MSSQL and one of key value and document databases like MongoDb, Dynamo Db, Casandra.
• Exposure to containers, microservices, distributed systems architecture, orchestrators and cloud computing.
• Comfortable with core programming concepts and techniques (e.g. concurrency, memory management)
• Enjoys working with algorithms and data structures (e.g. trees, hash maps, queues)
• Excellent communications skills and the ability to work with subject matter expert to extract critical business concepts.
• Ability to work and potentially lead in an Agile methodology environment.