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: 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: 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: 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.

EDUCATION AND/OR EXPERIENCE

Experience: 7+ years of hands-on data engineering experience, with meaningful time spent building pipelines and data models in production environments. Demonstrated experience working across both AWS and GCP — engineers who have worked deeply in one cloud and have real exposure to the other are a strong fit. Track record of building data infrastructure from limited foundations — not inheriting mature systems, but designing and building them. Experience working closely with analytics or business teams to translate data needs into engineering solutions. Comfort operating with a high degree of autonomy and incomplete specifications.

Technical Skills: AWS — S3, Lambda, EventBridge, Glue/Athena, AppFlow; pipeline design, deployment, and troubleshooting. GCP / BigQuery — dataset management, scheduled queries, partitioning and clustering, Standard SQL, performance optimization. SQL — advanced, across both Athena and BigQuery dialects; DDL/DML, window functions, complex transformations. Python — Lambda authoring, data transformation, scripting and automation. LookML — data modeling for Looker; building explores, dimensions, measures, and maintaining model integrity as underlying data evolves. GA4 → BigQuery export schema — understanding of the event model and how to work with the raw export. Infrastructure-as-code (Terraform or CloudFormation) — strongly preferred. dbt or a comparable transformation layer — strongly preferred.

How you work

Business-connected — you understand why the data you build matters and can articulate tradeoffs in terms stakeholders understand. Technically opinionated — you have views on the right way to build things and can defend them clearly. High ownership; you drive work to completion and flag blockers early rather than waiting. Clear communicator with both technical peers and non-technical stakeholders. Effective in a lean, fast-moving environment where the right answer often requires initiative, not instructions.

Education

Bachelor's degree in a quantitative field — Mathematics, Statistics, Computer Science, Economics, Engineering, or related — required. Advanced degree or relevant certifications are a plus.

BENEFITS

• Competitive salary
• Fully remote across India
• An outstanding collaborative work environment
• Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of the position