Data connectivity lead

Data Connectivity Lead

Key Responsibilities:

• Define and execute the product roadmap for AI tooling and data integration initiatives, driving products from concept to launch in a fast-paced, Agile environment.
• Translate business needs and product strategy into detailed requirements and user stories
• Collaborate with engineering, data, and AI/ML teams to design and implement data connectors that enable seamless access to internal and external financial datasets.
• Partner with data engineering teams to ensure reliable data ingestion, transformation, and availability for analytics and AI models.
• Evaluate and work to onboard new data sources, ensuring accuracy, consistency, and completeness of fundamental and financial data.
• Continuously assess opportunities to enhance data coverage, connectivity, and usability within AI and analytics platforms.
• Monitor and analyze product performance post-launch to drive ongoing optimization and inform future investments.
• Facilitate alignment across stakeholders, including engineering, research, analytics, and business partners, ensuring clear communication and prioritization.

Basic Qualification:

• Bachelor’s degree in Computer Science, Finance, or related discipline. MBA/Master’s Degree desired.
• 5 plus years of experience in a similar role

Required Qualifications:

• Strong understanding of fundamental and financial datasets, including company financials, market data, and research data.
• Proven experience in data integration, particularly using APIs, data connectors, or ETL frameworks to enable AI or analytics use cases.
• Familiarity with AI/ML data pipelines, model lifecycle, and related tooling.
• Experience working with cross-functional teams in an Agile environment.
• Strong analytical, problem-solving, and communication skills with the ability to translate complex concepts into actionable insights.
• Prior experience in financial services, investment banking, or research domains.
• Excellent organizational and stakeholder management abilities with a track record of delivering data-driven products.

Preferred Qualifications:

• Deep understanding of Python, SQL, or similar scripting languages
• Knowledge of cloud data platforms (AWS, GCP, or Azure) and modern data architectures (data lakes, warehouses, streaming)
• Familiarity with AI/ML platforms
• Understanding of data governance, metadata management, and data security best practices in financial environments.
• Experience with API standards (REST, GraphQL) and data integration frameworks.
• Demonstrated ability to partner with engineering and data science teams to operationalize AI initiatives.