Senior Data Engineer
Remote
Full time
About the project
It is a U.S.-based project focused on the digital sale and distribution of tickets for live entertainment, with a strong emphasis on theater, musicals, and cultural events. The platform allows users to discover shows, purchase tickets easily, and access special offers, including discounts and last-minute options, through a primarily mobile-first experience. It works closely with theaters and producers to optimize event commercialization and expand audience reach, combining standard-priced tickets with more accessible alternatives while strengthening the connection between audiences and live cultural experiences.
About the role
We are supporting one of our clients in the search for a Senior Data Engineer to join their team of Analytics and Data Engineers. This role will play a key part in building and maintaining the data foundation that enables informed business and product decision-making. The engineer will be responsible for designing and developing reliable, scalable data pipelines, as well as working across a wide range of internal systems, services, and APIs to transform raw data into trusted, analytics-ready datasets. This opportunity is well suited for an engineer who is comfortable operating in ambiguous environments, can quickly understand complex systems, and enjoys solving end-to-end data challenges — from source systems and instrumentation through transformations and delivery of metrics and reporting tables. The role involves close collaboration with Operations, Product, Finance, and Data stakeholders to ensure the client’s data remains accurate, accessible, and actionable, while also enabling the rapid integration of new data sources as the business evolves.
Key Responsibilities
- Build, maintain, and improve scalable batch and streaming data pipelines that ingest, transform, and deliver reliable datasets for analytics and reporting.
- Partner with teams across the organization to understand data needs and translate them into robust, scalable data models.
- Work directly with internal products and services (and sometimes messy or undocumented ones) to extract data via APIs, logs, databases, or events.
- Own the “last mile” of data enablement: ensuring data is not just collected, but clean, consistent, and usable in downstream tools.
- Implement data quality checks, observability, and alerting to detect issues early and reduce downstream incidents.
- Improve and standardize data definitions, metrics, and naming conventions to reduce ambiguity across teams.
- Build shared tools or frameworks to improve the productivity and quality of all data practitioners (Data Engineering, Analytics Engineering, Data Science).
- Contribute to and influence the direction for key infrastructure and framework choices for data pipelining and data management.
- Launch data platform features that have an immediate, measurable impact on the velocity of innovation and ultimate business growth.
- Develop deep expertise in one or more business domains to anticipate andproactively meet evolving data needs.
- Support investigations and debugging when pipeline outputs don’t match business expectations—and drive fixes at the source when needed.
Requirements
- Very high SQL proficiency, with experience in both analytical and transactional dat systems.
- Solid programming and system design skills for building robust, scalable, and extensible data solutions.
- Experience designing and developing large-scale, efficient batch and streaming data processing pipelines.
- Comfort working across languages/services as needed—you don’t need to be a specialist in everything, but you should be able to learn quickly and ship reliably.
- A pragmatic approach to data correctness: you value accuracy, but you also know how to iterate and improve without blocking progress.
- Experience designing pipelines with monitoring, retries, and clear failure modes (you build things that don’t silently break).
- Strong ownership mindset: you proactively identify pipeline risk, performance bottlenecks, or missing inputs and take initiative to resolve them.
- A passion for ensuring a great data end-user experience and driving data stewardship across the organization.
- Ability to analyze and reason about large datasets to identify data quality issues and other contextual insights.
What We Offer
- Physical activity covered by the company to promote a healthy lifestyle
- English classes to support your professional growth
- Sponsored training and learning opportunities
- Paid Time Off (PTO) for rest, balance, and recharging
- Your birthday off to celebrate your day
