Data engineer in advertising

Samba connects the advertising industry. Today, a trillion dollars of media flows through platforms that don’t talk to each other, and each one measures its own results. We built the independent alternative: consented first-party data and AI that give the world’s biggest advertisers, publishers, and platforms one clear view across all of it. The next era of advertising will run on AI agents, and those agents will need data they can trust. We’re building that foundation, and the agents that act on it. Join us and help build what the industry runs on.

• Lead the design and development of scalable, high-performance data pipelines and infrastructure that power Samba's analytics, and resolve complex technical issues in creative and effective ways.
• Lead the design, build, and maintenance of high-scale production datasets, delivering versioned outputs and reliable customer-facing reports.
• Manage the end-to-end lifecycle of data features, adding attributes, updating business logic, and executing safe rollouts (staging, performance check, production), including complex backfills and reprocessing.
• Architect efficient solutions for data ingestion, transformation, and storage, ensuring performance, reliability, and security, and proactively drive down compute and storage costs.
• Serve as technical lead for production incidents: investigate root causes, implement permanent fixes, and validate data recovery across the ecosystem.
• Enhance monitoring and observability of data processes, improving debugging, error detection, and system reliability at scale.
• Network with key contacts outside your area and advise others on complex matters, guide new policies and ideas, and mentor engineers to foster a culture of technical excellence.

• Typically 8+ years of related experience with a Bachelor's degree (6+ with a Master's, or 3+ with a PhD), or equivalent practical experience.
• Advanced Python and a deep understanding of distributed data processing frameworks like Apache Spark or PySpark.
• Must-have expertise in Apache Airflow and Databricks for orchestration and scalable data processing.
• Extensive experience with cloud-based data infrastructure (AWS, GCP) and modern data lake architectures.
• Strong knowledge of data modeling, database design, and query optimization for relational and non-relational databases.
• A proven track record of driving best practices for code quality, testing, and software design in data engineering.
• Able to adapt your communication style and use persuasion when delivering messages that relate to the wider business.

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