Lead Data Engineer

About the role

You will own how we scale the data platform that serves as the backbone connecting product, growth, finance, and customer experience to a single source of truth. You will lead the team responsible for the project lifecycle end to end, encompassing staging, intermediate layers, and data marts. You will set the technical direction and raise the team's bar for architecture, review, and delivery quality. You will own the CI/CD pipeline and the Snowflake platform that underpins it, ensuring stability and performance as the organization scales. You will design how the platform absorbs new sources and consumers as Todaytix Group expands under MARI and portfolio brands join the ecosystem. You will partner closely with product, growth, finance, and CX to translate business demands into robust data structures and pipelines. You will spend most of your time on architecture, technical strategy, and cross-functional leadership, with hands-on modeling reserved for deliberate, high-impact work. You will measure your success by the team's output and the business impact of the data platform, especially as AI tooling increasingly queries the data directly.

Key facts

What you'll do

Architect the ingestion and transformation layers that power event, ticketing, and financial data across Todaytix Group and MARI portfolio companies.

Define and enforce data modeling standards for intermediate and mart layers so that downstream consumers can rely on consistent semantics and definitions.

Lead the development and maintenance of CI/CD pipelines for data assets, ensuring rigorous testing, documentation, and traceability.

Partner with growth and product to design experiments and funnels, translating analytical requirements into scalable data structures.

Oversee the Snowflake environment, optimizing cost, performance, and security as data volume and query complexity increase.

Collaborate with finance and CX teams to deliver reliable reporting and insights that drive decisions on pricing, marketing, and experience design.

Champion the adoption of AI-ready data patterns so that queries against the platform can leverage large language models effectively and safely.

Own the roadmap for the project layer, prioritizing features and reliability improvements based on stakeholder needs and technical risk.

Mentor engineers and analysts, elevating the quality of code reviews, design documents, and operational runbooks across the data team.

Establish service-level objectives and monitoring for data pipelines to ensure reliability and quick detection of issues.

Translate business initiatives from portfolio brands into technical specifications that the platform can support at scale.

Drive data quality initiatives, defining checks and observability practices that prevent issues before they reach production dashboards.

Requirements

You must be based in the greater New York City area and eligible to work in the United States without sponsorship.

You must have a Bachelor's degree or equivalent practical experience, with a strong background in data engineering or a related field.

You must have extensive experience designing and operating data platforms, including pipelines, warehouses, and transformation layers.

You must have deep expertise in Snowflake, including modeling, performance tuning, and native features such as Snowpipe and streams.

You must have hands-on experience with CI/CD for data, including tools like Git, Airflow or similar orchestrators, and automated testing frameworks.

You must have strong SQL skills and experience optimizing complex queries across large, multi-source environments.

You must have proven ability to lead cross-functional initiatives and communicate effectively with both technical and business stakeholders.

You must be comfortable working in a fast-paced, high-growth environment where priorities evolve quickly and ownership is expected at all levels.

Nice to have

Experience working with event and ticketing data domains, including inventory, pricing, and transaction models.

Familiarity with AI and LLM workflows for analytics, including prompt engineering, retrieval-augmented generation, and guardrails for data security.

Experience contributing to open source data projects or publishing technical content that demonstrates thought leadership.

Practical notes

This full-time position requires candidates to be based in the greater New York City area.

You are expected to collaborate in the office a minimum of 2 days per week, with flexibility to choose where you work for the remainder of the week.