Senior Data Engineer

About Sayari: Sayari is the judgment infrastructure for trustworthy AI in economic security and commercial risk. The Sayari Commercial World Model resolves 11.7B+ primary-source records from 250+ jurisdictions forming the ground truth of global commerce. A Judgment Ontology, encoding over a decade of investigative tradecraft, and Superconductor, an agentic orchestration platform, deliver AI that reasons like an expert analyst, shows its work, and traces every finding to its source. Trusted by U.S. Customs and Border Protection, HM Revenue & Customs, and Fortune 500 enterprises, Sayari is used by thousands of professionals across 35+ countries to secure supply chains and dismantle illicit networks. Headquartered in Washington, D.C., with offices in London, Singapore, Tokyo, and Tel Aviv. POSITION DESCRIPTION As a Data Engineer at Sayari, you will be the engine behind the world’s most comprehensive commercial world model. You will join a high-autonomy team responsible for building and scaling the complex orchestration systems that transform billions of primary-source records into actionable intelligence. This is a role for a "builder" who respects the complexity of large-scale ETL and graph databases and is "PhD-curious" about the future of AI-native data products and modern orchestration. JOB RESPONSIBILITIES Design, build, and maintain scalable data pipelines using Python, Spark, and Airflow to support our core data acquisition and entity resolution engines. Collaborate cross-functionally with AI/ML and Product teams to implement new features and AI-native products. Proactively identify and resolve bottlenecks in our complex ETL processes, bringing a fresh perspective to refine and optimize our existing codebase. Contribute to a robust engineering culture through rigorous code reviews, unit testing, and clear communication of design decisions. Own the end-to-end delivery of roadmap tasks within two-week sprints, ensuring work meets high standards for quality, documentation, and performance. Participate in roadmap planning and story refinement, eventually taking ownership of major epics that drive our long-term product defensibility. SKILLS & EXPERIENCE Required 5 or more years of production data engineering experience, with clear ownership of systems you built and operated end to end Strong Python, with meaningful experience in a JVM language (Scala preferred) or willingness to ramp quickly Hands-on Snowflake experience, or equivalent depth in BigQuery or Redshift with demonstrated ability to transfer Experience deploying and operating AI or ML applications in production, including output validation, monitoring, and cost management at scale Orchestration experience with Apache Airflow or a comparable workflow tool Track record of operating production systems reliably, with comfort navigating failure, monitoring, and recovery Preferred Experience with Spark on Dataproc Serverless or other serverless Spark environments Familiarity with Kubernetes for deployment Experience with data quality tooling such as deequ, Great Expectations, or equivalent GCP experience (BigQuery, Dataproc, Cloud Storage) Experience leading or contributing to a data warehouse migration Background in team mergers or migrating a team onto a new operating process The target base salary for this position is $140,000-$160,000 plus company bonus and equity. Final offer amounts are determined by multiple factors including location, local market variances, candidate experience and expertise, internal peer equity, and may vary from the amounts listed above. Benefits: 100% fully paid medical, vision, and dental for employees and their dependents Generous time off; we observe all US federal holidays, close our office for a winter break (12/24-12/31), in addition to granting 18 PTO days and 10 sick days Outstanding compensation package; competitive commissions for revenue roles and bonuses for non-revenue positions A strong commitment to diversity, equity, and inclus