Braintrust · 8 hours ago

Data Engineer - W2 - US & Canada

United States

Full-time

Remote

Senior Level

5+ years exp

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Responsibilities

Develop, maintain, and optimize data pipelines: Build and support robust pipelines for data ingestion, processing, and transformation, ensuring high reliability and performance to meet evolving business needs.

Ensure data quality, accuracy, and consistency: Monitor, troubleshoot, and resolve issues related to data pipeline performance, data integrity, and consistency. Ensure accurate and timely data availability across ads data systems.

Support the creation and maintenance of reporting systems: Centralize key business metrics and marketplace metrics. Ensure these metrics are consistently tracked, reported, and accessible across teams.

Contribute to data visualization and reporting tools: Assist in implementing data visualization tools like Looker and Hex, ensuring seamless integration of data sources and actionable reporting for both technical and non-technical stakeholders. Continuously improve reporting data models to enhance scalability and ease of use.

Enhance internal data tools: Develop and maintain internal applications that streamline data analysis, making it easier for cross-functional teams to generate insights. Ensure these tools are optimized for performance and user-friendly.

Work closely with data engineering and data science teams to ensure accurate data collection and consistent advertiser channel history.

Collaborate across teams to ensure the effective integration of data tools and metrics for business tracking and analysis.

Troubleshoot data issues.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

ETL systemsPythonSQLData modelingData governanceAirflowData visualizationLookerTableauScalaSparkAds domain experienceCross-functional collaboration

Required

Bachelor’s or Master’s degree in a quantitative discipline: engineering, statistics, operations research, computer science, applied mathematics, etc.

5+ years of experience working with large-scale ETL systems, with a focus on building and maintaining clean, maintainable code (Python preferred) in a production environment.

Strong programming proficiency in Python, SQL, Spark, Scala, etc.

Experience with data modeling, ETL concepts, and maintaining data governance for large-scale structured and unstructured data.

Expertise with data workflows (e.g., Airflow), data modeling, and both front-end and back-end engineering for data systems.

Experience in data visualization and dashboard design, using tools such as Looker, Tableau, or other visualization libraries.

Proven ability to execute in a cross-functional environment, collaborating with engineers, data scientists, and other stakeholders.