Architect and build high-performance data solutions that directly power customer-facing features, utilizing the internal data platform (Snowflake, dbt, Kafka).
Lead the design and delivery of complex data projects independently, from initial discovery with stakeholders to production deployment and monitoring.
Partner with Product Managers and Business Leaders to translate customer needs into technical data requirements, ensuring "Data-as-a-Product" excellence.
Work embedded with Application Engineering teams to advocate for upstream data quality and ensure application architectures support downstream data needs.
Act as the "Lead Customer" for our internal Data Platform team—identifying gaps in the platform’s capabilities and contributing to its strategic roadmap based on product requirements.
Establish and evangelize standards for data modeling, observability, and performance within the product domain.
Design resilient, production-grade pipelines using DLT and Snowpipe that handle enterprise-scale workloads with low latency.
Own the domain’s dbt layer, ensuring code is modular, tested, and optimized for high-performance serving in Snowflake.
Guide and elevate Senior and Mid-level engineers on the team through code reviews, design docs, and technical coaching.

Requirements

8+ years of experience in Data Engineering, with a strong emphasis on building solutions for customer-facing products or applications.
Proven ability to lead large-scale projects from concept to completion with minimal supervision, navigating ambiguity across multiple teams.
Exceptional ability to evangelize data strategy to non-technical stakeholders and influence application engineers on data best practices.
Deep expertise in Snowflake, dbt, and Kafka for building real-world, high-value data products.
Strong Python and SQL skills, with a focus on building reusable libraries, automation, and CI/CD-driven workflows.
Experience working in a SaaS product environment, understanding how data latency and accuracy impact the end-user experience.
Advanced understanding of modeling for both analytical (OLAP) and application-support (high-concurrency) use cases.

Benefits

A discretionary bonus typically paid annually
Restricted Stock Units granted at time of hire
401(k) match and comprehensive employee benefits package

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

data engineeringdata modelingPythonSQLdbtSnowflakeKafkaCI/CDdata pipeline designautomation

Soft skills

leadershipcommunicationinfluencingevangelizingcollaborationproblem-solvingtechnical coachingproject managementstakeholder engagementnavigating ambiguity