Sr. DataOps Engineer, Data Platform

Top Dog Law is a nationally scaling personal injury firm that owns the client experience end to end, from marketing and intake through litigation. We've grown 2-3x year over year for three years running, and we're now building the operations, systems, and teams to scale without sacrificing quality or culture. We're fully remote, and we value ownership, open communication, and speed.

If you want to help build something exceptional, you'll feel at home here.

We're looking for a Senior Data Ops Engineer to own the operations, security, and cost of our data platform. We're migrating from Big Query to Snowflake, and you'll be the hands-on Snowflake expert who runs the platform and makes sure it stays secure, observable, and well managed as our data footprint grows with machine learning, AI, and structured and semi-structured data from AWS S3 and external vendor files.
This is a tactical, hands-on role supporting the data team and application teams across multiple business verticals. You'll bring data operations practices together in one place, and over time that scope will grow to include the Postgres and No

SQL databases our application teams use. We need deep Snowflake expertise combined with the breadth to look beyond it: how all of our data tools, vendors, access, and costs fit together, and opportunities to improve platform practices. You bring demonstrated experience managing complex data platforms and improving their operations.

• Run the platform. Own administration and day-to-day operations of Snowflake, including environments, warehouses, performance, and the operational side of our migration from Big Query.
• Standardize data operations. Define consistent operating practices for data ingestion from S3 and vendor files, structured and semi-structured data, and ML and AI workloads, using infrastructure as code and CI/CD for data.
• Extend platform practices to operational databases. Extend consistent operational practices to the Postgres and No
  
  SQL databases used by application teams, including backups, performance, and access.

• Secure the data. Apply least-privilege permissions, design appropriate data access roles, and integrate our data tools with SSO, with encryption and auditing for sensitive data.
• Manage data vendors and tools. Manage the external vendors and tools used by our data team, covering access, SSO integration, configuration, and licensing.

• Keep it observable and reliable. Build monitoring and observability across our data pipelines and platform, and define and run the incident management process, from response through root cause and follow-up.
• Improve cost transparency. Track and attribute spend across Snowflake and data tooling, provide teams with clear cost visibility, and drive optimization.

• Support multiple teams. Serve as the data operations point of contact for teams across business verticals, helping resolve operational challenges and establishing reusable practices and documentation.

• 7+ years of professional experience in data platform engineering, Data Ops, or Dev Ops, with a track record of operating production data platforms.
• Deep Snowflake expertise, including administration, role-based access control, warehouse management, performance, and cost.
• Strong security and access management skills, including least-privilege role design, SSO integration, encryption, and audit logging.
• Experience with AWS data storage and access, including S3, IAM, and the networking that governs data access.
• Experience building monitoring, observability, and incident management for data pipelines and platforms.
• Experience with cloud data cost visibility and management, including reporting spend clearly to technical and non-technical teams.
• Experience administering data vendor tools, such as ingestion, orchestration, BI, and data quality platforms.
• Experience with infrastructure as code and CI/CD for data workloads (e.g., Terraform, dbt deployments).
• Working experience operating relational and No
  
  SQL databases (e.g., Postgres).
• Broad understanding of the data ecosystem, including how platforms, tools, and processes integrate and where improvements are needed.
• Strong communication skills and a track record of supporting multiple teams and helping teams adopt shared practices.

• Experience migrating a data warehouse to Snowflake, or working knowledge of Big Query.
• Snowflake…