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# Data Engineer

- **Company:** CORTEX, INC.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $175,000.0 - $205,000.0
- **Contract:** Permanent contract
- **Skills:** Sql Data Warehouse, Artificial Intelligence, ARM Architecture, BigQuery, Information Engineering, Extract Transform Load (ETL), Python (Programming Language), Standard Sql, Information Technology, Vertica, Stream Processing
- **Published:** August 8, 2026
- **Apply:** https://job-boards.greenhouse.io/cortex/jobs/5380208008

## About the Role

* Bachelor's degree in Computer Science or related field, or equivalent practical experience
 * 4+ years of hands-on data engineering experience building and owning production pipelines
 * Proficiency with dbt, a cloud data warehouse (BigQuery or equivalent), and ETL/ELT tooling
 * Strong SQL and proficiency in a general-purpose language (e.g. Python) for pipeline and transformation work
 * Solid data modeling judgment with a focus on data quality, testing, and reliability
 * A bias toward mapping and rationalizing a messy environment before adding to it
 * Strong communication and collaboration skills, including with non-engineering stakeholders
 * Fluent, critical use of AI in day-to-day engineering, reviewing AI output as carefully as a teammate's PR
 * Experience with high-volume / streaming systems (ClickHouse, OpenTelemetry) or CDP / ETL tools (Segment, Hevo) is a plus
 * Previous experience at a startup is a plus

## Description

As a Senior Data Engineer, you'll own our internal data systems and pipelines. You will be responsible for the ingestion, transformation, and warehousing that power reporting across the company - consolidating a stack currently spread across Segment, Hevo, BigQuery, and Omni into a single, trustworthy source of truth, and laying the foundation for higher-volume data work as we grow. You'll partner closely with GTM operations to ensure our AI-driven automation & tools areis built on accurate, well-modeled data, including you'll own product analytics.
️ Responsibilities

 * Own data pipelines end to end - ingestion, transformation (dbt), warehousing (BigQuery), and delivery into reporting and BI (Omni)
 * Audit and map the existing data systems before rebuilding, then consolidate the stack toward a single source of truth
 * Build and maintain dbt models and transformation logic with tests, documentation, and clear contracts
 * Establish data quality, observability, and reliability practices so pipelines are maintained intentionally rather than reactively
 * Own product analytics: instrumentation and event tracking, data models for usage and adoption, and the metrics GTM and product teams rely on
 * Partner with GTM operations to consolidate reporting into a single tool and ensure we have the right data foundations for AI automation and tools.
 * Support research for external reports (e.g. the Engineering in the Age of AI benchmark report), partnering with marketing to source, validate, and pull the right data
 * Lay the groundwork for high-volume and streaming ingestion (e.g. telemetry / OpenTelemetry) as the product moves that way


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