Senior Data Engineer

Salary

Core Qualifications

Preferred Qualifications

Key Responsibilities

• •Design, build, and own end-to-end data pipelines and transformation workflows using dbt on BigQuery.
• •Develop scalable ELT models that support analytics, AI, marketing, and operational use cases.
• •Take ownership of existing pipelines while improving their reliability, maintainability, and performance.
• •Orchestrate and schedule data workflows using Dagster, ensuring pipelines are reliable, observable, and easy to operate.
• •Build robust testing, monitoring, alerting, and recovery processes across the data platform.
• •Improve pipeline architecture as workloads, data volumes, and business-critical use cases grow.
• •Partner with analysts and data scientists to deliver trusted, well-modeled, self-serve datasets in Hex.
• •Integrate and operationalize AI and LLM-driven workflows within the data platform.
• •Help internal teams move from ad-hoc data requests to scalable and reusable data products.
• •Build marketing attribution models that improve visibility into campaign performance and customer conversion.
• •Develop reverse ETL workflows that send accurate conversion data back to platforms such as Google Ads and Meta.
• •Integrate external data sources, advertising APIs, and data vendors into reliable production pipelines.
• •Establish and enforce standards for data quality, testing, documentation, observability, and deployment.
• •Optimize BigQuery workloads for query performance, scalability, and cost efficiency.
• •Contribute to data architecture decisions, mentor future hires, and help shape the technical direction of the data engineering function.