Technical Program Manager 2, Technical Solutions

Datadog’s Technical Solutions organization includes 1,200+ sales engineers, support engineers, post-sales experts, and solution architects. They run on an ecosystem of enterprise platforms and internal tools that directly shape how we serve customers. Technical Solutions Operations (“TSO”) owns that ecosystem. We manage the full lifecycle of the systems TS depends on: Zendesk, Jira, Confluence, and a growing portfolio of off-the-shelf and purpose-built tools. We do the work to operate, maintain, and evolve the platforms powering daily workflows across TS. When a vendor tool reaches its limits, we extend it through customization, integration, or targeted solution development, tapping internal partners across Datadog as needed. We’re looking for a systems engineer who wants to own enterprise platforms end-to-end. You go from understanding the business process, to designing the right solution (whether that’s configuration, integration, or code), to measuring whether it actually moved the needle.   At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.   What You’ll Do: * Own enterprise systems through their full lifecycle. You’ll be the technical owner for one or more platforms that TS relies on daily. That means understanding how the system is used, where it’s falling short, what’s coming from the vendor roadmap, and what needs to change. You drive improvements from assessment through implementation. * Engineer solutions that create leverage. Not every problem is solved by configuration. You’ll build and evolve enterprise systems, integrations, automations, and internal tools that multiply the effectiveness of 1,200+ technical experts. Where AI can make a solution smarter (e.g., intelligent routing, automated triage, agent-assisted workflows), you'll include AI in the initial design, not as an afterthought. * Contribute to the Datadog codebase when the problem calls for it. Some TS-specific features (e.g., support tooling, in-app experiences) ship into the same repos Engineering uses. This work is targeted and partnership-driven, and you’ll collaborate with Engineering teams to build and ship these capabilities. * Use AI to work faster and think bigger. AI coding tools are part of your daily workflow. You use them to ship faster, explore unfamiliar systems, and automate the tedious parts of your job. You can articulate how AI changes the way you work and help teammates adopt the same habits. * Solve business problems, not just technical ones. You’ll partner with TS leaders to understand what’s slowing their teams down, then engineer the fix. The best solutions aren’t always the most technically complex. They’re the ones that actually get adopted. * Own what you ship. Monitor, maintain, and iterate on systems in production. You understand your systems well enough to diagnose issues before anyone else does, from implementation and iteration through optimization and maintenance.    Who You Are: * 3-5 years of experience with enterprise platforms and production software. You’ve administered, extended, or integrated systems like Salesforce, Zendesk, Jira, or similar. You’ve also built software that real users depend on (web services, APIs, data pipelines, or applications). * Strong in Python, Go, or JavaScript/TypeScript. Bonus if you're a polyglot. You’ll work in whatever the problem demands. * Ability to work across the stack. You can build a backend service, wire up a frontend, design an API, and set up the CI/CD pipeline to ship it. * Demonstrated fluency with AI coding tools. You use Copilot, Claude, or similar daily and can articulate how it changes the way you work. * Experience building AI-powered features. You’ve worked with LLMs, embeddings, RAG pipelines, or agent frameworks. * Systems thinking. You design reliable, maintainable, scalable solutions that integrate with multiple upstream and downstream systems that improve the long-term health of our tech stack. * Experience contributing to a large shared codebase with established engineering practices (code review, CI/CD, feature flags, observability) * Background in technical support tooling or customer-facing business systems * Experience in a high-growth B2B SaaS environment   Datadog values people from all walks of life. We know not everyone will meet all the above qualifications on day one. That’s okay. If you’re passionate about technology and want to grow your experience, we encourage you to apply.   Benefits and Growth:  * Best-in-breed onboarding * Generous global benefits * Intra-departmental mentor and buddy program for in-house networking * New hire stock equity (RSUs) and employee stock purchase plan (ESPP) * Continuous professional development, product training, and career pathing * An inclusive company culture, able to join our Community Guilds and Inclusion Talks Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. 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. The reasonably estimated yearly salary for this role at Datadog is: $110,000—$162,000 USD ---------------------------------------------------------------------------------------------------------------------------------- About Datadog:  Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center. ---------------------------------------------------------------------------------------------------------------------------------- Equal Opportunity at Datadog: Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.  Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications.  Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.

Role Overview This role serves as the data leader and technical authority for Customer Success data at Toast. You will own the strategy and execution of CS data modeling initiatives -- redesigning the CS data model from the ground up and defining how data is accessed, queried, and served across the organization.   The CS data model needs to work reliably in two modes: as a structured foundation for dashboards, reporting, and operational metrics, and as a well-documented, trustworthy layer that AI systems can query consistently. Building for both -- and making deliberate architectural decisions about when each approach is appropriate -- is central to this role.   This is an embedded role, sitting inside the CS organization. CS data problems are business problems first -- understanding how customers are being supported, where friction exists, and what patterns predict risk or opportunity requires close proximity to the teams asking those questions. This role is positioned to build that context directly and translate it into data architecture decisions.   You will lead a small team of two senior data and analytics engineers to start, with room to grow as the function matures.   What You'll Do Data Architecture & AI Data Strategy * Own the redesign of the unified CS data model, connecting data across Care, CX, Enablement, and CSS teams and source systems including our new contact center platform. * Define and execute the AI data strategy for CS -- specifically, how AI accesses, queries, and interacts with the data model. This means making active architectural decisions about when to pre-calculate and structure data versus when to allow dynamic AI retrieval, with predictability and consistency of outputs as the governing constraint. * Build and maintain a documentation layer that functions as a first-class artifact -- not an afterthought. Reliable AI data access depends on well-structured, accurate documentation, and this person will treat it that way. * Develop and apply a clear framework for when AI is the right tool versus traditional data approaches. Part of the job is pushing back when AI is unnecessary or introduces reliability risk.   Platform & Pipeline Development * Lead the data integration for the contact center platform migration, ensuring clean, well-modeled contact data flows into the CS data layer from day one. * Design and optimize pipelines for analytics, reporting, and AI/ML-driven use cases. * Establish testing, monitoring, and alerting as standard practice across CS pipelines -- freshness checks, completeness validation, anomaly detection. Stakeholders should never be the first to know something is broken.   Leadership & Cross-functional Partnership * Manage and mentor two senior data and analytics engineers, providing clear direction and building a high-performance team from the ground up. * Serve as the primary data architecture partner for CS analytics and operations leaders, translating business problems into data model and tooling decisions. * Collaborate closely with cross-functional peers in CS analytics, enterprise data infrastructure, finance, and business technology to align on KPI definitions, data lineage, and governance standards. * Represent CS data interests in enterprise governance forums, ensuring security, compliance, and architecture standards are met.   Enablement & Governance * Ensure CS data is accurate, accessible, and trusted by the teams who depend on it -- from strategic OKRs down to operational dashboards. * Maintain a shared KPI dictionary, data lineage map, and self-service analytics framework in partnership with centralized data teams. * Establish clear SLAs for data delivery and processes for ongoing data quality monitoring.   What We're Looking For Required Qualifications * 10+ years of experience in data platform, data modeling, or analytics engineering roles, with at least 3 years in a leadership capacity. * Experience designing data models with AI consumption in mind -- structuring for retrieval versus pre-calculation tradeoffs, ensuring predictability of outputs, and understanding that documentation is infrastructure, not overhead. * Hands-on experience with modern data stack tools -- Snowflake, dbt, or equivalent -- including building or maintaining a semantic layer that ensures consistent metric definitions across BI tools, notebooks, and AI agents. * A track record of treating pipelines like software: automated tests, schema validation, freshness and completeness monitoring, and changes that go through review before they reach production. You have been burned by silent data failures and build accordingly. * Proven ability to diagnose systemic data quality and architecture problems and redesign from the ground up -- not just patch on top of what exists. * Strong cross-functional communication skills -- you can translate complex data architecture decisions for non-technical business stakeholders.   Preferred Qualifications * Experience working in Customer Success, SaaS, or customer-facing operational analytics environments. * Familiarity with Snowflake and modern orchestration frameworks (dbt, Airflow, or equivalent). * Background that skews toward data modeling and transformation work -- you think in terms of data models, schemas, and semantic layers rather than services and application infrastructure. * Experience with BI tools and dashboarding. * Familiarity with real-time data streaming technologies (Kafka, Kinesis, or equivalent).   Who Will Thrive Here * You are energized by greenfield work. This role is building something new, and the fingerprints you leave on the data model and AI strategy will be visible and lasting. * You are comfortable with a lean team today. Two direct reports to start, with room to grow -- this is not a role for someone who needs org size to feel impactful. * You have the judgment to advocate for the right use of AI, including knowing when not to use it. The goal is a trustworthy, reliable data layer -- not AI for its own sake. * You are a builder first. Strategy matters, but so does the ability to roll up your sleeves and make decisions at the implementation level.   The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits. You can learn more about how we align pay with local labor markets in our Geographic Pay Zone Philosophy. Zone A $217,000—$347,000 USD Zone B $188,000—$301,000 USD Zone C $170,000—$272,000 USD How Toast Uses AI in its Hiring Process Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focused on your conversation. All hiring decisions are made by people. To learn more: https://careers.toasttab.com/ai-in-hiring Our Approach to Hybrid Working We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the hospitality community, regardless of location. Please visit the Locations page on our career site to learn more about our in-office expectations by region: https://careers.toasttab.com/locations-toast Diversity, Equity, and Inclusion is Baked into our Recipe for Success At Toast, our employees are our secret ingredient—when they thrive, we thrive. The restaurant industry is one of the most diverse, and we embrace that diversity with authenticity, inclusivity, respect, and humility. By embedding these principles into our culture and design, we create equitable opportunities for all and raise the bar in delivering exceptional experiences. We Thrive Together We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the restaurant community. To learn more about how we work globally and regionally, check out: https://careers.toasttab.com/locations-toast. Apply today! Toast is committed to creating an accessible and inclusive hiring process. As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact candidateaccommodations@toasttab.com. ------ For roles in the United States, it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.