ABOUT TRIBUTE TECHNOLOGY:

At Tribute Technology, we make end-of-life celebrations memorable, meaningful, and effortless through thoughtful and innovative technology solutions. Our mission is to help communities around the world celebrate life and pay tribute to those we love. Our comprehensive platform brings together software and technology to provide a fully integrated experience for all users, whether that is a family, a funeral home, or an online publisher. We are the market leader in the US and Canada, with global expansion plans and a growing international team of more than 400 individuals in the US, Canada, Philippines, Ukraine and India.

ABOUT YOU:

This role is for a senior data engineer who is equally comfortable building pipelines and modeling the data that flows through them — and who brings enough business judgment to own a priority end-to-end without needing every decision validated.

Tribute Technology runs a hybrid AWS and GCP data environment with limited existing infrastructure. There is real work to build here. You will connect new data sources, design the models that make that data usable, and deliver pipelines that serve both the eCommerce Operations team and the broader Tribute data organization. The Director of Data will provide technical direction and business context; you will own the execution path from there.

If you are looking for a role with well-scoped tickets and established systems, this is not it. If you have the experience to assess a problem, form a technical view, and build the right solution — this is.

WHAT YOU WILL DO:

• Build and maintain data pipelines:
  • Design, build, and maintain data connectors and ingestion pipelines across Tribute's AWS and GCP environment — including AWS AppFlow, Lambda, EventBridge, S3, Athena, and BigQuery.
  • Own pipelines end-to-end: from source connection and ingestion through transformation, modeling, and delivery to downstream consumers in Power BI, Looker, and Looker Studio.
  • Build for reliability and maintainability — instrument pipelines appropriately, handle failure gracefully, and leave systems in a state others can work with.
  • Identify fragile or missing infrastructure and make a case for what to build next based on business impact.

• Model the data:
  • Design data models that reflect how the business actually works — not just what is technically convenient to store.
  • Build and maintain LookML models that make data accessible and consistent for analysts and business users.
  • Write and optimize BigQuery SQL including scheduled queries, partitioned and clustered tables, and transformation logic that scales.
  • Work closely with the eCommerce Operations team and other data consumers to understand how data will be used and model it accordingly.

• Own your work:
  • Take a business priority and determine the right technical path to deliver it — without requiring approval on every step.
  • Connect your engineering decisions to downstream outcomes: you understand why the data matters and who depends on it.
  • Surface technical recommendations proactively — on architecture, tooling, sequencing, or risk — and communicate them clearly to the Director of Data and stakeholders.
  • Operate effectively in an environment where requirements are sometimes incomplete and the right answer requires judgment, not just execution.