Technical Product Manager, Data and Internal Products

SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. The Technical Product Manager will lead internal initiatives within SentiLink’s Tech organization, focusing on data-intensive systems and ensuring clarity, quality, and coordinated execution across various teams.

Responsibilities:

• Own the product vision, roadmap, and execution for internal technical initiatives, with a strong focus on data‐intensive systems and foundational datasets
• Lead cross-functional efforts to improve the quality, reliability, and usability of internal systems, including datasets, shared services, and internal platforms
• Drive long-term initiatives to future-proof internal data and technology assets, ensuring they scale with evolving product, analytics, and operational needs
• Partner with engineering, data science, solutions analytics, and product stakeholders to understand use cases, clarify requirements, and identify interdependencies
• Manage prioritization across competing internal demands, balancing immediate impact with long-term strategic value
• Translate complex internal needs into clear, actionable specifications and ensure alignment across teams
• Apply structured project management to initiatives with multiple teams, ambiguous problem spaces, and intricate technical dependencies
• Define and track success metrics for internal systems and datasets, such as quality, completeness, latency, reliability, and stakeholder satisfaction
• Communicate roadmap, progress, risks, and tradeoffs to internal stakeholders at all levels

Requirements:

• 5+ years of experience with data-heavy or platform-oriented products, with a focus on ML/Data Science strongly preferred
• Hands-on experience working with large datasets, ideally in distributed or big-data environments (e.g., Spark, Databricks, BigQuery, Snowflake, similar)
• Strong understanding of big data concepts, data pipelines, data cleaning/normalization, and data modeling
• Demonstrated ability to partner effectively with engineering, data science, and analytics teams on deeply technical problem spaces
• Experience driving large internal initiatives with multiple stakeholders and managing substantial cross-functional dependencies
• Proven ability to structure ambiguous requirements, prioritize effectively, and deliver predictable execution on complex technical programs
• Excellent communication skills, with the ability to explain technical concepts to diverse audiences and facilitate alignment across teams
• A forward-looking, durability-focused mindset—ensuring internal systems and datasets are built for scale, maintainability, and long-term adaptability