Data Engineer

Trupanion•Seattle, WA

1d•$130,000 - $150,000•Hybrid

About The Position

The Data Engineer is responsible for designing, building, and optimizing reliable, scalable, and auditable data systems on our modern Databricks Lakehouse platform hosted in Microsoft Azure. In this role, you will be on the cutting edge of data engineering—thinking, designing, and documenting data marts. We are looking for a dynamic, forward-thinking engineer who is passionate about the latest developments in the data ecosystem and places the utmost importance on data quality and governance. You will work closely with your team and peers to drive the evolution of continuous delivery, automated quality frameworks, and agile data products. This position is open across the United States with a preference for those in Seattle or the East Coast time zone. Seattle candidates will have a hybrid remote/in-office schedule where you will work from our casual, pet-friendly office at least 3 days a week.

Requirements

Bachelor’s level degree or higher in Computer Science, Engineering, or equivalent practical experience.
Minimum 2+ years of experience designing, building, and enhancing high-performance pipelines (ETL/ELT) and building optimized Data Marts across the enterprise.
Minimum 2+ years of deep technical experience within a Databricks-centric environment leveraging: Delta Lake & Apache Spark (PySpark / SparkSQL), Unity Catalog for data governance, lineage, and documentation, Delta Live Tables (DLT) or similar orchestration tools.
Proven experience implementing robust data quality, testing, and monitoring frameworks (e.g., Great Expectations, Databricks Expectations, or custom data quality gates) to ensure flawless data integrity.
Experience required with software and infrastructure change management, CI/CD pipelines (Azure DevOps/GitHub Actions), and source code control.

Nice To Haves

Passion for the latest industry trends, including the Medallion Architecture (Bronze/Silver/Gold), Data Contracts, and decentralized data design.
Strong conceptual thinker who doesn't just build, but actively designs and documents data assets, schemas, and definitions directly within Unity Catalog.
Hands-on experience implementing data pipelines for a variety of flows, including batch data integrations, real-time streaming analytics (Structured Streaming), and big data analytics.
Experience setting up comprehensive logging, alerting, and monitoring solutions for Spark jobs and data pipelines.
Thrives in a fast-paced, Agile software development environment, with a strong proactive drive to learn and adopt new tools and features as the Databricks ecosystem evolves.

Responsibilities

Responsible for ensuring continuous, accurate data availability by monitoring, troubleshooting, and optimizing batch and real-time streaming pipelines across the Medallion architecture to deliver stable, high-availability data feeds with minimal downtime.
Responsible for delivering query-ready Gold-layer data marts, dimensional models, and aggregate tables by partnering directly with Data Analytics and Data Science teams to map business requirements into high-performance user-facing schemas.
Responsible for protecting the integrity of the Lakehouse by configuring automated validation gates and alerts at the ingestion stage to catch and block corrupt or non-compliant source data.
Responsible for maintaining flawless data integrity and trust across all data products by writing, deploying, and maintaining automated data quality test suites and expectations for key transformation stages.
Responsible for ensuring all data assets are easily discoverable by documenting schemas, applying metadata tags.
Responsible for serving as an autonomous data engineering partner to downstream teams by proactively investigating data discrepancies, resolving support tickets, and aligning business definitions to unblock analysts and data scientists.