Lead Data Engineer

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Ticketure

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2016

☁️ SaaS

🤝 B2B

💰 $5.5M Series A - Ticketure on 2015-09

SaaS • B2B

Ticketure is a cloud-based ticketing, point-of-sale, and membership management platform for museums, zoos, aquariums, gardens, galleries and high-volume visitor attractions. It unifies ticketing, membership, donations, in-venue sales, timed entry and analytics into one connected system to grow revenue across admissions, memberships and fundraising. The platform supports advance and on-site sales, capacity control, timed programmes, distribution integrations, and reporting; Ticketure reports processing 206M+ tickets, $1. 4B+ annual revenue processed, and 875K active memberships managed across 150+ cultural and visitor attractions worldwide.

📋 Description

• Design, build, and maintain reliable data pipelines, models, and reporting assets within our Snowflake-based platform, powering internal analytics, tenant-facing reporting, data shares, AI/NLQ use cases, and usage-based billing • Partner cross-functionally with Engineering, Product, Finance, and Client Success to understand business and tenant needs, ensuring data is ingested, transformed, and exposed accurately • Champion strong engineering practices, version control, CI/CD, automated testing, documentation, and infrastructure as code, along with data quality checks, observability, and alerting to keep critical pipelines reliable • Provide hands-on technical leadership on platform architecture, tooling, governance, and cost management, leading code and design reviews and driving improvements to engineering standards • Lead complex initiatives end to end, from problem definition through delivery, managing priorities, communicating trade-offs, and surfacing risks early • Influence technical decisions by presenting clear options and evidence, and help teams self-serve trusted data through strong documentation and discoverability • Use AI thoughtfully to boost engineering productivity, code quality, testing, documentation, and problem-solving

🎯 Requirements

• Significant hands-on experience in data engineering roles, designing, building and maintaining production-grade ETL/ELT pipelines, data models and data products • Strong SQL skills and practical experience with Snowflake or a similar cloud data platform, including performance, security and access control considerations • Experience working in a SaaS, multi-tenant or similarly complex and governed data environment, including secure data access, tenant isolation, data quality and PII considerations • Practical experience using modern data engineering practices, including version control, automated testing, CI/CD and repeatable code-based delivery

🏖️ Benefits

• Competitive base annual salary, commensurate with experience • Annual discretionary bonus based on performance and company success • Incentive equity opportunity • 3.5% employer KiwiSaver contribution • Home office stipend • Annual leave that increases with tenure • Paid volunteer leave • Working abroad opportunities • Learning and development support, including reimbursement for approved educational expenses • Flexible working arrangements