Senior Data Engineer, Filevine

• 5+ years of professional data engineering or backend engineering experience, with a proven track record of delivering production-grade data systems that drive measurable business outcomes
• Significant hands-on experience operating a modern cloud data warehouse in production (e.g., Snowflake, BigQuery, Redshift, Databricks, Synapse, or equivalent) — including performance tuning, warehouse and cost management, role-based access control, and orchestration of warehouse-native compute (stored procedures, UDFs, streams/tasks, or equivalent)
• Demonstrated experience building with Agentic AI or LLM-powered systems in production — e.g., RAG pipelines, tool-using agents, MCP servers, warehouse-native LLM functions (such as Snowflake Cortex, BigQuery ML, or Databricks AI), or comparable frameworks
• Expertise in advanced SQL and Python for building reliable, well-tested data pipelines and transformations
• Experience with modern data modeling and transformation tooling such as dbt, including testing, documentation, and backward-compatible model design that supports self-service analytics
• Experience with workflow orchestration (Airflow, Dagster, or similar) and cloud-native deployment on AWS, Azure, or GCP
• Strong fundamentals in data modeling (dimensional, star/snowflake schemas), distributed systems, performance tuning, and data quality / observability principles
• Professional experience with modern software development methodologies: Agile/Kanban, Git, CI/CD, and DevOps
• Excellent written and verbal communication skills, with the ability to explain complex technical and data concepts to both technical and non-technical stakeholders
• B.S., M.S., or Ph.D. in Computer Science, Information Systems, Engineering, or a related field — or equivalent professional experience

Desirable

• Optimize and improve Filevine's production usage of Snowflake and Cortex features — including warehouse management (usage, sizing, monitoring, etc.), clustering, query performance tuning, cost governance, and storage efficiency
• Own and evolve our agentic data modeling and natural language data retrieval (text-to-sql) capabilities: build and curate semantic models, refine prompts, expand verified question libraries, and measure answer quality so that natural-language analytics get more accurate over time
• Design and build batch and streaming data pipelines that ingest, transform, and model data from Filevine's product, CRM, billing, and telemetry systems into trusted, well-documented data products
• Build the data foundations that power agentic AI workflows and LOIS — including feature pipelines, retrieval datasets, and low-latency serving paths for LLM-based reasoning over customer data
• Establish reliability and governance standards including data quality checks, lineage, monitoring, incident response, access control, and PII handling consistent with our compliance posture
• Partner with product and engineering stakeholders to define event contracts, model business concepts (matters, firms, users, billing) consistently, and reduce ambiguity across downstream consumers
• Lead the evaluation and adoption of emerging tools across the modern data stack, recommending right-fit solutions that align with Filevine's strategic and security goals
• Provide technical mentorship within the Data Engineering team, contribute to code reviews and design documents (DDs/ADRs), and help raise the bar on data engineering practice at Filevine
• Participate in on-call rotations to maintain SLAs for production data pipelines and analytics surfaces