Data Engineer

Stakeholder Engagement & Requirement Gathering: Partner with business stakeholders across Analytics, Operations, GTM, and G&A to understand problem statements and translate them into clear data requirements.

Data Modeling & Transformation: Design and build dimensional and analytical data models in Snowflake using dbt (Cloud/Core) that serve as the single source of truth for business domains. Develop, test, and maintain dbt models following best practices — modular layering (staging, intermediate, marts), documentation, and data tests. Optimize SQL queries and dbt models for performance using Snowflake features like clustering, materialization strategies, and query profiling.

Pipeline Scheduling & Deployment: Own scheduling and orchestration of dbt jobs, ensuring reliability, observability, and SLA adherence. Own CI/CD workflows for dbt and pipeline deployments using GitHub Actions — automated testing, linting, and promotion through environments. Work with the Data Platform team on AWS resource provisioning (via Terraform) needed to support ingestion and pipeline infrastructure.

• Data Quality & Analysis: Implement data quality checks and freshness tests within dbt to proactively catch issues before they reach consumers. Perform exploratory data analysis to validate source data, understand distributions, and surface anomalies during scoping and build phases.