> Markdown version of [/jobs/ext/4654020-remote](https://www.wearedevelopers.com/jobs/ext/4654020-remote). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Remote

- **Company:** Consumer Edge
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $175,000 - $210,000
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, BigQuery, Data Architecture, Information Engineering, Data Sharing, Data Systems, Data Warehousing, Cursor, Programming Tools, Distributed Systems, Python (Programming Language), Machine Learning, SQL Databases, Data Streaming, Claude Code, Snowflake, Technical Debt, AI Coding Agents, Backend, Apache Kafka, Data Management, Data Delivery, Entity Resolution, Data Pipelines, User Identification, Databricks, Programming Languages
- **Published:** November 10, 2026
- **Apply:** https://www.builtincolorado.com/job/staff-data-engineer/12142954?handler=ApplyRedirect

## About the Role

* 8+ years in data engineering or backend data systems, including production pipelines on high-volume data (consumer data is a plus)
 * Ad tech or martech experience with identity and audience data
 * Hands-on identity resolution experience, such as entity resolution or match tables, and familiarity with common ad tech identifiers
 * Experience with advertising data
 * Expert SQL and Python, with deep BigQuery or Snowflake experience and a modern stack such as dbt and Airflow
 * A track record of setting technical direction across teams, and clear communication with engineers and business leaders
 * Comfort using AI coding tools such as Claude Code, Cursor, or Codex as an everyday part of your work

Nice to have

 * Data clean room experience
 * Streaming pipelines with Kafka or Pub/Sub
 * Building AI developer tooling: agent harnesses, MCP servers, evals, or CI guardrails
 * Background in ad tech, martech, or consumer data products
 * Experience building for privacy and governance: consent, opt-outs, deletion, and state privacy laws

## Description

We're hiring a Staff Data Engineer to set the technical direction for identity and audience data in our data products. You'll design how our data connects across sources and partners, and build the pipelines our data products depend on, working with data science, product, and fellow engineers.
What you'll do

 * Own identity data. Design identity data models and matching logic, and keep them accurate, auditable, and current.
 * Build partner data mappings. Build and maintain identifier mappings with external partners, and report match quality and coverage.
 * Build data pipelines. Build and run the production pipelines behind our data products.
 * Build privacy in. Build consent, opt-out, deletion, and access controls into identity data, working with legal and security.
 * Set the quality bar. Create data quality frameworks, monitoring, and anomaly detection for pipelines that carry billions of rows.
 * Set technical direction. Lead design reviews and build-versus-buy decisions, and mentor data engineers through design and code reviews.
 * Lead how the team builds with AI. Work AI-first every day, and build the agent harnesses, shared skills, and guardrails that make AI-generated work safe to ship., Remote
United States
175K-210K Annually
Senior level
175K-210K Annually
Senior level
Database
Lead the technical direction for audience data products and build high-volume pipelines for audience creation, partner data onboarding, identity mapping, and external data delivery. Mentor engineers, oversee design reviews and build-versus-buy decisions, and develop AI-enabled engineering tooling with appropriate guardrails. Collaborate with data science, product, engineering, and external partners.
Top Skills: AirflowAPIsBigQueryCi/CdClaude CodeCursorDbtGithub CopilotInfrastructure As CodePythonSnowflakeSQL, Fanatics, Own the architecture and technical direction of scalable data platforms, including Python pipelines, Airflow orchestration, Snowflake, Databricks, and AWS systems. Establish standards for reliability, testing, governance, security, monitoring, and data delivery. Lead complex incident resolution, cost optimization, design reviews, and platform decisions while partnering cross-functionally. Mentor engineers, influence roadmaps, reduce technical debt, and support hiring and organizational development.
Top Skills: AirflowAmazon S3SparkAWSCi/CdData CatalogingData LineageDatabricksDatadogDbtKafkaLaunchdarklyMongoDBPii MaskingPostgresPythonRbacSegmentSnowflakeSQLTableau
Capital One