Key skills
PythonGitPostgreSQLBigQueryGraph databasesSparkAirflowDjangoScalaScrapyLLM tuningAI engineeringAIMLLLMETLData EngineeringUnit TestingAgileCommunication
About this role
Sayari is the judgment infrastructure for trustworthy AI in economic security and commercial risk. As a Data Engineer, you will build and scale orchestration systems that transform billions of records into actionable intelligence, collaborating with cross-functional teams to implement features and optimize ETL processes.
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
Requirements:
- Professional proficiency in Python and experience contributing to shared codebases using Git (branching, PRs, code reviews)
- 3+ years of experience working in Data Engineering
- Demonstrated experience working with relational databases (PostgreSQL/BigQuery) and an interest in or familiarity with graph databases
- Familiarity with distributed computing (Spark) or a strong desire to master it
- Strong collaborative skills and the ability to work effectively in an Agile, sprint-based environment
- A 'self-directed' orientation: ability to move tasks from 'assigned' to 'complete' with high autonomy and clear communication
- Experience with Django, Scala, or Scrapy
- Hands-on experience with workflow orchestration tools like Airflow
- Experience or strong interest in LLM tuning, deployment, and AI engineering best practices
- Experience working with international or non-English datasets
- Prior experience working with high-scale, complex data pipelines