Data Engineer - VP
875 3rd Ave Fl 10 New York City, NY 10022 US
Job Description
As a Data Engineer - VP on our Data and AI team, you'll play a key role in advancing the firm's goals by delivering innovative and scalable solutions. Your primary focus will be designing and implementing Data and AI systems to meet diverse business needs, and you may also be involved in analyzing potential investments.
Key Responsibilities:
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Project Delivery: Lead the creation and implementation of Data, AI, and Engineering projects. Apply a rigorous, hypothesis-driven approach to design solutions, collaborate with cross-functional teams, and ensure that development and deployment emphasize delivering value.
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Agile Execution: Deliver results rapidly and iteratively on high-pressure projects, demonstrating the ability to adapt quickly to shifting business needs and priorities.
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Innovative Solutions: Utilize modern platforms (e.g., Azure, AWS, GCP), technologies (e.g., Python, Spark, SQL, DBT), and tools (e.g., Power BI) to develop innovative solutions, integrating intellectual property into reusable software.
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Structured Problem-Solving: Manage disparate requirements with a high tolerance for ambiguity, leveraging strong problem-solving skills and exceptional stakeholder engagement.
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Analytical Communication: Translate complex analytical findings into clear insights for senior business executives, breaking down complex issues into understandable components.
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Storytelling: Present practical insights compellingly and effectively to various audiences.
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Reputation Building: Establish yourself as a trusted technologist and authority on Data and AI both within and outside the organization. Demonstrate broad technological expertise, challenge existing practices, and invent new analytical approaches to address business challenges. Build a reputation for reliability and strong stakeholder relationships.
General:
- Bachelor’s degree in a STEM field or equivalent.
- 10+ years of hands-on experience in delivering Data solutions in production environments.
- Exceptional intellectual curiosity, problem-solving skills, and team effectiveness.
- Strong ability to communicate ideas and solutions clearly to stakeholders.
- Experience managing end-to-end data solutions to support various AI/ML use cases.
Programming:
- Expertise in SQL and one additional language (Python, Java, Scala).
- Deep understanding of data structures, runtime, and memory complexities.
- Skilled in code optimization and writing reusable, efficient libraries.
- Proficiency in code review, providing feedback, and enforcing best practices for source code management.
Data:
- Advanced knowledge of at least one relational database (e.g., MySQL, PostgreSQL).
- Expertise in OLAP vs OLTP solutions and various storage solutions (Row Store vs Columnar Store).
- Proficiency in creating ERD diagrams and designing complex data models (e.g., star schema, galaxy schema).
- Knowledge of data privacy and security best practices.
Cloud:
- Proficiency with at least one cloud platform (e.g., Azure) and familiarity with others.
- Skilled in cloud storage, file storage, and cloud services (e.g., Azure Functions, API Management, Orchestration, Messaging queues, Kafka).
- Familiarity with cloud monitoring and logging.
Deployment:
- Proficient in version control (e.g., Git), containers (e.g., Docker), APIs, and orchestration.
- Experience with CICD pipelines and deploying APIs to serve model results, with familiarity in standard Python backend frameworks (e.g., Flask, Django).