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Lead Manager I 2c Engineering Code Coverage in United States

2,537 active opportunities · Updated October 2026

Explore current lead manager i 2c engineering code coverage jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 Boston, Massachusetts, United States· Full-time
✓ Quality checkedCompany trend -93.3%

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Are you passionate about helping organizations unlock the power of AI through modern data architecture? Snowflake is looking for a customer-facing Solution Engineer who combines strong technical depth with executive presence and a passion for innovation. In this role, you’ll partner with Sales to guide customers from raw data to real AI impact — architecting scalable solutions, delivering compelling demos, and influencing complex buying decisions across executive and technical audiences. Location: Candidate MUST be located in or near Boston. What You’ll Do Lead customer conversations on AI strategy and data modernization. Design and demonstrate scalable data and AI solutions using SQL and Python. Support enterprise Proof of Concepts from concept to value realization. Translate complex technical concepts into measurable business outcomes. Navigate objections and competitive dynamics in high-stakes sales cycles. Leverage AI tools to personalize demos, accelerate preparation, and enhance delivery. What You Bring Strong SQL proficiency and experience with modern data warehousing. Experience using Python for analytics or ML workflows. Familiarity with AI/ML concepts, including Generative AI and LLMs. Exceptional communication skills across technical and executive audiences. Abil

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📍 Menlo Park, California, United States· Full-time
✓ Quality checkedCompany trend -93.3%

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About the Team The Finance Data Science team owns the forecasting systems that power Snowflake’s revenue planning and long-term financial strategy. Our work supports corporate planning, executive decision-making, and investor reporting, and we partner closely with Product and Sales to understand customer behavior and product impact. We operate at the intersection of machine learning, statistical research, and corporate finance, building production-grade forecasting infrastructure that is foundational to how the company plans and operates. The Role As a Senior Data Scientist, you will independently lead high-impact modeling initiatives and build production-ready forecasting systems for core financial metrics. You will work on complex, open-ended problems at the intersection of machine learning and business strategy, translating real-world financial questions into rigorous, scalable models. What You’ll Do Design and implement advanced time-series and probabilistic models (e.g., hierarchical models, state-space models, Bayesian approaches, multivariate forecasting). Contribute to internal tooling and shared infrastructure that enables scalable forecasting and analytics. Establish best practices for model evaluation, backtesting, uncertainty quantification, and scenario simulat

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