Job Description

Locations

• New York, NY, United States

Salary

Skills Required

• or deploying AI-first analytics: AI-powered workflowsintermediate
• modern data stackintermediate
• or deploying AI agentsintermediate
• analytics engineeringintermediate
• financialintermediate
• Datadog's productsintermediate

Required Qualifications

• 6+ years in product analytics, data analytics, or a related field, with 2+ years managing or leading a team. (experience, 6 years)
• A strong track record partnering across functions (Product, Finance, Engineering, Data) and aligning stakeholders with different priorities toward shared outcomes. (experience)
• Proven ability to partner directly with product managers as their analytics partner, turning product questions into analysis that informs decisions. (experience)
• Fluent in SQL and comfortable in a modern data warehouse and BI tooling. You can go from raw data to a defensible answer yourself, not just direct others to do it. (experience)
• Hands-on experience building or deploying AI-first analytics: AI-powered workflows, agents, or tooling that speed up real analytical work. Professional use of AI tools such as Claude, including prompt design and putting AI into day-to-day analysis. (experience)
• Experience communicating with and presenting to senior leadership at the VP+ level, both in writing and in live settings. (experience)
• Comfortable in ambiguous environments where you define the approach, prove value quickly, and iterate, rather than maintain an existing playbook. (experience)
• Able to lead through influence rather than authority, building trust and driving outcomes across teams you do not directly manage. (experience)
• 6+ years in product analytics, data analytics, or a related field, with 2+ years managing or leading a team. (experience, 6 years)
• A strong track record partnering across functions (Product, Finance, Engineering, Data) and aligning stakeholders with different priorities toward shared outcomes. (experience)
• Proven ability to partner directly with product managers as their analytics partner, turning product questions into analysis that informs decisions. (experience)
• Fluent in SQL and comfortable in a modern data warehouse and BI tooling. You can go from raw data to a defensible answer yourself, not just direct others to do it. (experience)
• Hands-on experience building or deploying AI-first analytics: AI-powered workflows, agents, or tooling that speed up real analytical work. Professional use of AI tools such as Claude, including prompt design and putting AI into day-to-day analysis. (experience)
• Experience communicating with and presenting to senior leadership at the VP+ level, both in writing and in live settings. (experience)
• Comfortable in ambiguous environments where you define the approach, prove value quickly, and iterate, rather than maintain an existing playbook. (experience)
• Able to lead through influence rather than authority, building trust and driving outcomes across teams you do not directly manage. (experience)

Preferred Qualifications

• Experience supporting a product management org or working inside a Product function. (experience)
• Familiarity with the modern data stack (for example dbt, Snowflake, semantic layers) and with product data and CRM systems. (experience)
• Experience building or deploying AI agents or automated analytical workflows using current frameworks. (experience)
• A background in analytics engineering or data platform work. (experience)
• Experience with financial and revenue data (ARR, cohort analysis) and partnering closely with Finance. (experience)
• Familiarity with Datadog's products and services. (experience)
• Experience supporting a product management org or working inside a Product function. (experience)
• Familiarity with the modern data stack (for example dbt, Snowflake, semantic layers) and with product data and CRM systems. (experience)
• Experience building or deploying AI agents or automated analytical workflows using current frameworks. (experience)
• A background in analytics engineering or data platform work. (experience)
• Experience with financial and revenue data (ARR, cohort analysis) and partnering closely with Finance. (experience)
• Familiarity with Datadog's products and services. (experience)
• Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan. (experience)

Responsibilities

• Guide and grow the Internal Product Analytics team. Manage, coach, and develop a team of data analysts. Set priorities, hold a high bar for quality, and make sure the team's output is trusted across the Product org.
• Partner directly with the PM org. Work side by side with the PMs your team serves to frame the questions that matter, shape the analysis, and make sure the answers reach them in a form they can act on.
• Own the recurring analytics the PM org runs on. Business reviews, feature request analysis, usage and adoption tracking, and pricing analysis. Make this work consistent, repeatable, and fast so PMs get answers when they need them.
• Build AI-first analytics. Design and ship AI-powered workflows and agents that do the heavy lifting of analysis, from data querying to synthesis to reporting. Set the standard for how the team uses AI so analysis scales without simply adding headcount.
• Partner across functions. Work with Finance, Data Platform, Engineering, and Revenue teams to align on definitions, source the right data, and turn raw signals into decisions. Build trust with partners who do not report to you.
• Turn data into decisions for leadership. Query product, CRM, and financial data to surface the insights that matter, then present them clearly to PMs and senior leadership so they can act with confidence.
• Set the standard for product analytics across the org. Define the metrics, definitions, and analytical frameworks that leadership and every PM rely on, and own them as the single source of truth the Product org trusts.
• Guide and grow the Internal Product Analytics team. Manage, coach, and develop a team of data analysts. Set priorities, hold a high bar for quality, and make sure the team's output is trusted across the Product org.
• Partner directly with the PM org. Work side by side with the PMs your team serves to frame the questions that matter, shape the analysis, and make sure the answers reach them in a form they can act on.
• Own the recurring analytics the PM org runs on. Business reviews, feature request analysis, usage and adoption tracking, and pricing analysis. Make this work consistent, repeatable, and fast so PMs get answers when they need them.
• Build AI-first analytics. Design and ship AI-powered workflows and agents that do the heavy lifting of analysis, from data querying to synthesis to reporting. Set the standard for how the team uses AI so analysis scales without simply adding headcount.
• Partner across functions. Work with Finance, Data Platform, Engineering, and Revenue teams to align on definitions, source the right data, and turn raw signals into decisions. Build trust with partners who do not report to you.
• Turn data into decisions for leadership. Query product, CRM, and financial data to surface the insights that matter, then present them clearly to PMs and senior leadership so they can act with confidence.
• Set the standard for product analytics across the org. Define the metrics, definitions, and analytical frameworks that leadership and every PM rely on, and own them as the single source of truth the Product org trusts.

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