Senior Data Engineer
Quick Summary
Filevine is a Legal AI company delivering Legal Operating Intelligence for the future of legal work. Grounded in a singular system of truth, Filevine brings together data, documents, workflows,
- 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.
- 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
Nice to Have
~1 min read- Hands-on Snowflake experience, including Snowpipe, streams/tasks, data sharing, and cost/governance tuning at scale.
- Experience with Snowflake Cortex Analyst specifically, including authoring and iterating on semantic models and verified queries.
- .NET / C# experience, or familiarity with reading and integrating against a .NET-based application backend.
- Experience using modern UI development tools, particularly Svelte or React
- Experience supporting machine learning workflows: feature stores, training datasets, or real-time scoring infrastructure.
- Experience in SaaS or product-led growth environments, including product analytics and revenue/usage telemetry.
- Infrastructure-as-code experience (Terraform), containerization (Docker, Kubernetes), and deployment (Octopus).
- Familiarity with the legal tech domain, document-heavy data, or working with unstructured data at scale.
- Track record of mentoring engineers and contributing to hiring and team-building.
- You will be a core builder of the data and AI foundations that LOIS and Filevine's product surfaces are built on.
- Your work will directly shape how legal professionals query, reason over, and act on their data — and will determine how fast, accurate, and trustworthy our agentic AI experiences become.
Location & Eligibility
Listing Details
- Posted
- May 13, 2026
- First seen
- May 13, 2026
- Last seen
- May 13, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 87%
- Scored at
- May 13, 2026
Signal breakdown
Filevine is a cloud-based legal technology company providing case management, document management, and automation tools for law firms and legal departments. [1, 4, 30] It aims to simplify and elevate complex legal work. [5, 19]
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Senior Data EngineerUSD 160000–190000