Top Tech Jobs & Startup Jobs

Coordinates Engineering Excellence initiatives involving technical debt, AI-SDLC adoption, developer experience, modernization, quality, and tooling. Maintains milestones, dependencies, risks, decisions, actions, status, and completion criteria. Partners with Engineering, Product Delivery, initiative owners, vendors, and cross-functional teams to track execution, escalate issues, support reporting, and transition completed work to operational owners.

Provides practical legal advice across commercial, product, privacy, data security, regulatory, and corporate matters. Drafts and negotiates SaaS agreements, MSAs, SOWs, NDAs, and DPAs; supports incident response, data governance, AI and analytics initiatives, corporate policies, audits, investigations, and dispute resolution. Requires a U.S. law degree, bar admission, and at least two years of relevant legal experience.

Designs, develops, and owns BI dashboards, visualizations, data models, calculations, and reporting solutions primarily in TIBCO Spotfire, with Power BI support. Oversees BI architecture, standards, version control, deployments, and data quality while partnering with engineering and product teams. Mentors developers, guides design decisions, and independently manages deliverables in a multi-tenant life sciences data platform.

Own the strategy, roadmap, requirements, and delivery of enterprise data management and data product capabilities. Partner with customers, engineering, data, analytics, QA, and business teams to define data integration, quality, governance, reference data, and analytics-ready solutions. Lead discovery, prioritization, Agile delivery, UAT, release readiness, and stakeholder alignment while supporting Life Sciences and Net Revenue data use cases.

Analyzes and certifies conversational AI queries and answers against source data. Improves prompts, semantic layers, taxonomies, metadata, and data models while partnering with Product, Data Science, Engineering, QA, and business owners. Documents business logic, writes technical requirements, identifies recurring quality issues, supports roadmap planning, and creates accuracy test cases and product communications.

Analyze and certify conversational AI queries and answers against source data. Improve prompts, semantic layers, taxonomies, metadata, and labeling so Prism accurately interprets life sciences data. Collaborate with Product Management, Data Science, Engineering, QA, and business owners to identify data-quality issues, define technical requirements, document business logic, create accuracy test cases, and inform the product roadmap.

Analyzes and certifies AI-generated answers for Prism, a conversational analytics platform for life sciences data. Reviews prompts and queries, validates results against source data, improves semantic layers and data models, identifies recurring quality issues, documents business logic, writes technical requirements, and collaborates with Product Management, Data Science, Engineering, QA, and business stakeholders.

Supports daily operational processes by validating and reconciling data, investigating discrepancies, resolving issues, maintaining documentation, participating in customer and internal meetings, conducting quality reviews, supporting onboarding and system enhancements, and identifying workflow improvements. The role collaborates across teams, manages multiple priorities, and develops knowledge across operational functions.

Own the multi-quarter roadmap and strategy for Channel Data products. Analyze complex, high-volume data, lead customer discovery, prioritize initiatives, define requirements using AI tools, manage risks and dependencies, oversee release readiness, and communicate product decisions to senior leaders. Partner closely with engineering, data science, managed services, customers, and delivery teams to drive product outcomes and planning.

Designs, develops, and owns business intelligence dashboards, visualizations, analyses, and reporting solutions, primarily in TIBCO Spotfire and also Power BI. Responsibilities include data modeling, calculations, performance tuning, deployment workflows through GitHub, data quality collaboration, BI standards, risk identification, mentoring, and independent decision-making across a multi-tenant Life Sciences data platform.