Lead Data Engineer

About TodayTix Group: TodayTix Group (TTG) is the global e-commerce leader for cultural experiences, designing frictionless discovery and purchase journeys through innovative product design and industry-leading technology. Our portfolio of brands––including TodayTix, New York Theatre Guide, London Theatre, Show-Score, Arthouse, Arthouse London, and Secret Cinema––connects millions of customers with the best in live entertainment. Powered by vast data and insights, TTG helps theatres, producers, and cultural institutions reach highly engaged audiences and unlock meaningful revenue, transforming how tickets are sold across the world. In 2025, TTG entered a new chapter as part of MARI, the global events and experiences company powering world-defining live experiences. Together, we’re expanding our reach, deepening our impact, and accelerating a shared vision to redefine the event lifecycle through seamless discovery, purchase, and engagement. Life at TodayTix Group We thrive in a nimble, growth-oriented environment where adaptability, curiosity, and a bias toward action help us stay ahead of the curve. We move quickly, iterate often, and expect everyone to take ownership of their impact - because we're building the future of live events, and there’s no script for what comes next. New joiners are set up for success with a 90-day onboarding journey, complete with clear goals and measurable milestones. We believe feedback fuels growth, so we hold twice-yearly performance reviews focused on impact and development. Above all, you’ll be working alongside a team of collaborative, passionate, and kind humans - people who love theatre and live experiences, and who support each other just as much as they challenge each other to do great work. We are seeking outstanding applicants of all backgrounds to join our team to bring new voices, talent, and perspectives to the table. We encourage all to apply. About the Role: We’re looking for a Lead Data Engineer to join TodayTix Group and own how we scale our data platform — the backbone connecting product, growth, finance, and CX to a single source of truth, plus increasingly the substrate AI tooling across the company queries directly. You’ll lead the team that owns the project end-to-end — staging, intermediates, and marts — plus the CI/CD pipeline and Snowflake platform underneath it. This is a technical leadership role, not a heads-down modeling one — most of your time goes to architecture, review, technical strategy, and cross-functional leadership, with hands-on modeling a deliberate minority. You lead by setting direction, raising the team’s bar, and owning delivery, quality, and stakeholder trust across a high-demand roadmap. The foundation is built — your job is what gets built on top of it as the org scales. TTG is expanding as part of MARI, bringing new portfolio companies’ event and ticketing data onto the platform; PxT (our partner-facing product) is growing its surface area; and the business keeps adding markets and brands. You’ll design how the platform absorbs that growth — new sources, new consumers, higher stakes — without the architecture buckling. If you thrive in a fast-moving, high-ownership environment, measure your impact by the team’s, not just your own, and care as much about business impact as technical craft, we’d love to hear from you — especially if, like the rest of the team, you reach for AI by default. Please note: This full-time position and qualified candidates must be based in the greater NYC area. We encourage collaboration by working a minimum of 2 days per week in the office, with flexibility to choose where you work for the rest of the week. What Success Looks Like: The platform scales, it doesn’t strain → New portfolio events, new surfaces, and new markets onboard onto the existing staging/intermediates/marts pattern without one-off hacks or a rebuild. Data people trust by default → Certified marts stay accurate and documented as volume and source count grow; breaking changes get caught by CI and dbt tests, not discovered by a stakeholder in a dashboard. A faster, more autonomous team → Engineers ship models confidently without you reviewing every line; your reports are visibly leveling up. Architecture that holds → Your design decisions — dynamic tables vs. incremental models, how a new portfolio company’s data enters the model, orchestration choices — hold up as sources and consumers multiply, and design flaws get caught in review, not production. Trust through ownership → Stakeholders across product, growth, finance, and CX bring you problems, not tickets, because you communicate early and their reporting hasn’t broken under them. What You'll Do: Own the data platform end-to-end — the dbt project (staging → intermediates → marts), CI/CD, and the Snowflake infrastructure it runs on. Design and lead the onboarding of new data sources onto the platform as TTG scales, so growth doesn’t mean architectural debt. Partner with data consumers — product, growth, finance, CX, and incoming portfolio teams — to model new sources cleanly rather than bolt them on under deadline pressure. Run intake and prioritization across a high-demand roadmap where reporting, growth analytics, and AI-tooling initiatives compete for the same team’s time — sequence against business objectives, and say no well. Protect data quality systematically — dbt tests, contract-enforced schemas, and CI that catches breaking changes before they reach a dashboard or an AI agent. Set technical direction for the warehouse and give the kind of code review that makes data engineers better — spotting model design flaws before they ship. Lead and grow the team — 1:1s, feedback, and career development. Build the factory, not just the models: keep pushing AI into how the team works, and support the org’s growing use of AI agents as direct consumers of the warehouse you build. We're Looking for Someone With: A track record of leading engineers. 8+ years in data engineering (or software engineering with a heavy data bent), including leading a team — formally or informally — and growing the engineers around you. This is the core of the role. Deep SQL and dbt expertise. You’ve built and scaled a dbt project in production — models, tests, macros, contracts — and reason about warehouse cost and performance, not just correctness. Cloud data warehouse depth. Hands‑on experience with Snowflake or a comparable MPP warehouse (Redshift, BigQuery). Experience scaling a data platform through growth — onboarding new business units, acquisitions, or data sources onto an existing model without rearchitecting from scratch. (M&A / multi‑entity data integration experience is directly relevant given the evolving company structure). Full‑stack data platform judgment. Comfortable across ingestion (CDC/replication from operational databases, event pipelines), transformation (dbt), and consumption (BI tools, reverse ETL, AI/agent access) — even where you’re not the one writing every layer. Strong architecture and code review. You set technical direction through sound data‑model design and give review that makes engineers better. Stakeholder management. You partner with product, finance, growth, and CX — translating messy source data into models people trust, and setting expectations as priorities shift. A product and business mindset. You measure success by the decisions your data enabled, not rows modeled. AI fluency. You already reach for AI to write and review data models, and you’re comfortable with AI agents as first‑class consumers of the warehouse you build. You don't need to tick every box. If most of this sounds like you, we'd love to hear from you. Nice to Have: Experience with a customer data platform (CDP) and identity resolution across multiple event sources — directly relevant to unifying data across our portfolio companies. Experience with CDC / replication tools feeding a warehouse from an operational database (MySQL, Postgres) Experience with Looker/LookML or another BI semantic layer. Experience in e-commerce, ticketing, or a marketplace business with high‑cardinality partner/catalog data. Experience building or supporting AI/LLM‑facing data products — a chatbot, a RAG pipeline, an agent with database access. Experience with GitHub Actions‑based CI/CD for data pipelines. $195,000 - $215,000 a year Salary ranges are determined by competitive market data for our size, stage, and industry, experience and location of the applicant, and our internal salary banding, which is reviewed at least annually. We aim to be as transparent, equitable, and fair as possible. Qualified candidates and our Talent Acquisition team will discuss salary and benefits in the initial conversation, and final salary will be determined after candidates complete the interview process. We expect that the majority of candidates who are offered roles at TTG fall healthily throughout the range based on the above factors. To learn about the Perks and Benefits outside of the salary, please check out our "Good to Know" section! Good to Know: Hybrid work environment (blend of in-office and at-home days) Up to 4 weeks per year of flexible 'work from anywhere' Healthcare, vision, and dental plans, with generous contributions from the company Life and disability insurance Paid Parental Leave Generous 401(k) Matching Flexible Paid Time Off Free membership to One Medical Group & Employee Assistance Program Annual Professional Growth Budget Employee donation matching Employee Referral Program Pre‑Tax Flexible healthcare spending account (FSA), Dependent Care FSA and Commuter Benefits TodayTix Group is proud to be an equal opportunity employer, committed to fostering a workplace that celebrates diversity and inclusion. We welcome candidates of all backgrounds and do not discriminate based on race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital or veteran status, pregnancy, disability, or any other characteristic protected by law. We are also committed to providing reasonable accommodations for applicants and employees based on their religious practices, mental health, or physical needs. For information on our US employee and applicant privacy policy, click here. For more information about the data we collect and retention periods, please see our Data Collection Notice here. #J-18808-Ljbffr