
Own the architecture and roadmap for the Snowflake data platform, ingestion pipelines, and reporting infrastructure.
Set technical standards for data modeling, schema design, query patterns, testing, and observability across the data team.
Lead design reviews and make build-vs-buy calls on tooling (ELT platforms, orchestration, BI, replication).
Drive multi-quarter initiatives such as warehouse migrations, schema redesigns, and reporting platform consolidations.
Design and build scalable ELT/ETL pipelines using Python, SQL, Airbyte, and similar tools - including ingestion from external partner data sources (e.g., third-party catalog/match providers) and internal product databases.
Build and maintain reporting suites delivered via internal tooling, scheduled jobs, and email
Tune Snowflake performance and spend: warehouse sizing, clustering, caching, query rewrites, and storage management.
Own the operational health of business-critical dashboards - including cache strategy, latency targets, and incident response on Highest-priority data issues.
Establish SLAs and monitoring for pipelines and dashboards; lead root-cause investigation for data-quality and freshness incidents.
Partner with backend engineering on application-to-warehouse integration and event/data contract design.
Operate and evolve data workloads on AWS (S3, Lambda, RDS, IAM) and integrate with the broader application infrastructure.
5+ years of experience in Software Engineering / Data Engineering, with at least 2 years in a senior, tech-lead, or staff-equivalent capacity owning a data platform or major data domain.
Deep, production-level expertise with data platforms - including schema design, performance tuning, RBAC, cost optimization, and operational practices (credential rotation, replication, recovery).
Expert-level Python and SQL for production pipelines, transformations, and tooling.
Strong track record designing and operating ELT/ETL systems (Airbyte, Fivetran, dbt, custom Python - any equivalent stack).
Experience building reporting and analytics products end-to-end: ingestion → modeling → delivery (BI, embedded dashboards, scheduled email, internal tools).
Solid AWS experience (S3, Lambda, RDS, IAM) and familiarity with infrastructure-as-code and CI/CD for data workloads.
Demonstrated ability to lead technical initiatives that span multiple teams and quarters.
Excellent communication - comfortable presenting trade-offs to engineering leadership and translating business asks into technical scope.
Results-driven company culture that encourages a balanced lifestyle.
Flexible remote working environment.
Above-market remuneration, based on experience and skill level, paid in USD.
Work on cutting-edge platform problems - the kind that meaningfully improves the life of every engineer on the team - in a collaborative and innovative setting.