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Ocrolus is an AI-powered workflow and analytics platform for lenders, processing nearly one million credit applications monthly. The company serves 400+ customers including Better Mortgage, Brex, Enova, PayPal, Plaid, SoFi, and Square, combining state-of-the-art AI models with human-in-the-loop verification to capture financial document data with over 99% accuracy.
In this Senior Business Analyst role, you will design and implement data architecture and models that optimize data processes and improve efficiency across the organization. You'll build and maintain reliable, scalable data pipelines in Snowflake or similar platforms, ensuring data availability and trustworthiness. Your technical responsibilities include writing and optimizing complex SQL queries to extract and analyze large datasets, using Python to integrate and automate data workflows, and creating clear visualizations (Tableau, Sigma, or similar) to support data-driven decision-making.
Beyond technical execution, you'll collaborate with cross-functional teams to translate business requirements into technical specifications, manage key stakeholder relationships, understand their data needs, and deliver timely, actionable insights. You'll also optimize and streamline existing analytics processes to improve reporting capabilities and identify patterns and root causes in data.
Ocrolus is a remote-first, fast-growing company with a culture grounded in empathy, curiosity, humility, and ownership. The team values diverse perspectives and is committed to fostering an inclusive workplace.
**Requirements:**
- Bachelor's or Master's degree in Data Science, Computer Science, Information Systems, or related field
- 4+ years of experience in data analytics, data architecture, and process optimization
- Expert-level SQL: complex query writing, query and database performance tuning, large dataset management
- Strong analytical and problem-solving skills; ability to break down ambiguous business questions and find patterns in large datasets
- Experience designing scalable data models and platforms (dimensional, star/snowflake schemas) with sound pipeline management
- Strong working knowledge of Python for data integration, manipulation, and automation
- Clear communication with both technical and non-technical teams
**Preferred:**
- Experience with Snowflake and ELT/orchestration tools (dbt, Airflow)
- Git/CI-CD for analytics code
- Data quality, observability, and governance practices (validation checks, lineage, SLAs)
- Snowflake cost and performance tuning (warehouse sizing, clustering, query profiling)
- AI-driven analytics: hands-on use of LLMs and AI tools (Snowflake Cortex, Claude) for text-to-SQL, automated insights, or anomaly detection
