Analytics Engineer at SeatGeek | New York

SeatGeekNew York, New York

On-site Full-time $121K/yr - $175K/yr

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Key Responsibilities:Collaborate with fellow Analytics Engineers to develop robust data pipelines utilizing SQL and Python-based ETL frameworks for effective data acquisition, processing, and delivery across SeatGeek. Engage with diverse stakeholders, including Data Scientists, Analysts, Data Platform Engineers, and Software Engineers, to understand data use cases and product requirements for R&D teams. Design and thoroughly validate high-performing data models that facilitate analysis within a data warehouse environment. Assist in triaging and debugging on-call requests as part of a rotational on-call schedule with the Analytics Engineering team. Empower AI-driven stakeholder data analysis by creating LLM-friendly DWH schemas, developing domain guides, and enforcing standardized naming conventions across all tables for AI agent consumption. Collaborate with Analytics leadership to formulate a strategy around BI tooling, ensuring stakeholders have seamless access to usable data.

About the job

Join SeatGeek, where we believe live events are transformative experiences that bring people together. With our innovative technology and customer-centric approach, we are revolutionizing the ticketing industry.

We are seeking a passionate Analytics Engineer to become a vital member of SeatGeek’s Data team. In this dynamic role, you will collaborate with business stakeholders to facilitate effective data management and insightful analyses. As an Analytics Engineer, you will be instrumental in discovering, extracting, storing, cataloging, modeling, and processing our vast amounts of data. You will take charge of our analytics data layer and will work on extracting data from production databases and third-party sources, designing efficient data models, and orchestrating jobs in Airflow to produce clean, well-documented datasets that are ready for analysis. This role requires strong collaboration, as you will maintain relationships with analysts and production engineers to unlock the value of our data. Your contributions will play a crucial part in our mission to position SeatGeek as the premier destination for live event enthusiasts.

The live event sector is experiencing unprecedented growth, and we are poised to capitalize on this opportunity. Our teams require actionable metrics and feedback loops to inform critical business decisions. If you are someone who is passionate about leveraging data to drive decision-making, this is the perfect role for you.

About SeatGeek

At SeatGeek, we are on a mission to enhance the live event experience through innovative technology. Our commitment to our fans and their experiences drives us to simplify and modernize the ticketing industry. Join us as we redefine how people connect through live events.

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Mar 3, 2026

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Full-time|On-site|New York, New York, United States

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Apr 23, 2026

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Apr 14, 2026

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Analytics Engineer at SeatGeek | New York

SeatGeek

Full-time|$121K/yr - $175K/yr|On-site|New York, New York

Join SeatGeek, where we believe live events are transformative experiences that bring people together. With our innovative technology and customer-centric approach, we are revolutionizing the ticketing industry.We are seeking a passionate Analytics Engineer to become a vital member of SeatGeek’s Data team. In this dynamic role, you will collaborate with business stakeholders to facilitate effective data management and insightful analyses. As an Analytics Engineer, you will be instrumental in discovering, extracting, storing, cataloging, modeling, and processing our vast amounts of data. You will take charge of our analytics data layer and will work on extracting data from production databases and third-party sources, designing efficient data models, and orchestrating jobs in Airflow to produce clean, well-documented datasets that are ready for analysis. This role requires strong collaboration, as you will maintain relationships with analysts and production engineers to unlock the value of our data. Your contributions will play a crucial part in our mission to position SeatGeek as the premier destination for live event enthusiasts.The live event sector is experiencing unprecedented growth, and we are poised to capitalize on this opportunity. Our teams require actionable metrics and feedback loops to inform critical business decisions. If you are someone who is passionate about leveraging data to drive decision-making, this is the perfect role for you.

Mar 11, 2026

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Data & Analytics Engineer at Tandem | New York

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Full-time|On-site|New York office

Join Our Mission at TandemTandem stands as a transformative opportunity to revolutionize the way we introduce innovative therapies into the market. Our journey is notably de-risked due to:Rapid Organic Growth: With established product-market fit, we are experiencing swift expansion. Tandem supports thousands of new patients daily, gains traction through physician referrals, and collaborates with leading biopharma companies worldwide.AI-Driven Business Model: Our operations are fundamentally enhanced by AI, creating a robust business that thrives as foundational models evolve. We are cultivating resilience through two-sided network effects that amplify over time.Premier Investors: Backed by top investors such as Thrive Capital, General Catalyst, and Accel, we have the confidence to build an extraordinary team of engineers and operational experts.Our foremost priority is to scale in response to market demand. We seek highly motivated, resourceful individuals to help us enhance our capacity and accelerate our growth. Our pace is fast, and we aim to move even quicker.All full-time positions are based in our New York office. Discover more about our workplace culture in the last section of this page.Role OverviewAs a Data & Analytics Engineer at Tandem, you will be instrumental in establishing the data infrastructure that underpins our operations, measurement, and growth strategies. You will design and maintain our core data models, pipelines, and reporting frameworks, ensuring that key stakeholders have access to reliable, decision-grade data at the pace required for our fast-moving environment. This cross-functional role has a significant impact, collaborating closely with product, operations, growth, and leadership teams to develop systems that facilitate quicker, more informed decision-making across the organization.You will also help shape our data and analytics engineering practices, including metric structuring, code review processes, pipeline management, and scalability considerations. Your contributions will directly influence aspects ranging from product usage insights to operational performance and client reporting in life sciences.This role is demanding, with a high degree of autonomy and responsibility. We expect you to take ownership and fully commit to Tandem's success. If you are eager to learn, possess a low-ego mindset, and are excited about impactful work that propels both company growth and your career advancement, we want to hear from you.

Jul 31, 2025

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Senior Analytics Engineer

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Full-time|On-site|New York, New York, United States

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Apr 13, 2026

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Engineering Manager, Analytics Environment

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Full-time|$152K/yr - $190K/yr|Hybrid|New York, NY

Join The New York Times as an Engineering Manager, spearheading the Analytics Environment team within our Data Platform division. In this pivotal role, you will cultivate a dynamic, secure analytics and data prototyping environment that empowers users across the organization to unearth insights and conduct in-depth analyses. This position is based in our vibrant New York City headquarters and offers a hybrid working model.

Feb 5, 2026

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Analytics Engineer

RightWay Healthcare

Full-time|$130K/yr - $140K/yr|Remote|New York, NY or Remote

ABOUT THE ROLE: RightWay Healthcare is seeking an innovative Analytics Engineer to contribute to the design and development of a cutting-edge PBM Financial Risk Engine. This engine will integrate claims data, contract terms, pricing, and utilization metrics to enhance financial forecasting, risk evaluation, and performance tracking. The ideal candidate will have a robust background in dbt and analytics engineering, thriving at the crossroads of healthcare economics, PBM operations, and data modeling. You will play a crucial role in shaping and refining our financial risk engine data models, incorporating new data sources, optimizing existing ones, and ensuring that data is presented in a manner that facilitates efficient reporting and drives analytics innovation. This position will involve delivering and analyzing PBM financial data for diverse analytics applications within our Unified Data Warehouse (UDW) and implementing AI and ML solutions to generate impactful healthcare insights. WHAT YOU’LL DO: Utilize your hands-on analytics and data expertise to address complex, dynamic financial and operational challenges using PBM data. Design, develop, and maintain scalable, analytics-ready data models (mainly in dbt) that drive the PBM financial risk engine, utilizing claims, eligibility, pricing, rebates, guarantees, and contract data from our Unified Data Warehouse (UDW). Transform intricate PBM contract and pricing structures (e.g., plan paid vs. member paid, rebates, guarantees, caps, fees, exclusions) into clear, auditable data models that facilitate financial analysis and risk evaluation. Collaborate closely with underwriting, finance, client success, and PBM operations teams to comprehend financial assumptions, risk factors, and reporting needs, converting them into dependable metrics and models. Create curated financial and risk data marts and semantic layers that empower self-service analysis for forecasting, scenario modeling, and executive reporting. Take ownership of core financial KPIs and risk metrics end-to-end, from raw claims and contract inputs to production-grade models, ensuring consistency and traceability. Establish automated data quality checks, reconciliations, and controls to validate financial outputs, ensuring alignment with source systems and contractual logic. Continuously enhance data models and warehouse performance to accommodate large-scale claims volumes and time-sensitive financial analyses. Contribute to data governance by setting modeling standards, documentation, and guidelines that support auditability, explainability, and long-term maintainability. Effectively communicate complex financial insights to stakeholders.

Mar 6, 2026

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