Responsibilities
- Develop and enhance data pipelines and analytical tools for improved scalability and performance
- Take ownership and advance core platform components, analytics engineering tooling, reusable patterns, and automation to elevate team capabilities
- Contribute to an AI-powered composable agentic delivery system automating the analytics lifecycle from context to merged pull requests
- Create and manage semantic models serving as a trusted, reusable base for analytics and AI applications organization-wide
- Develop internal AI agents and data-grounded tools with RPC-based integrations via MCP servers
- Design and apply cost management strategies for shared data assets, pipelines, and computational resources
- Establish and deploy scalable patterns for data ingestion, replication, and transfer across systems
- Promote innovation by exploring emerging technologies and keeping abreast of industry developments
- Provide technical leadership to guide the professional growth of team members
- Collaborate with stakeholders to address business challenges through technical solutions
- Construct scalable data models to analyze critical aspects of the business
- Expand the collection of dbt patterns and macros to support flexible and extensible data architectures
- Enhance data observability and pipeline reliability using tools such as Monte Carlo
- Set scalable standards and patterns for analytical application development in Hex
- Lead working groups, define requirements, and manage projects through all phases
- Keep thorough documentation of data pipelines, processes, and best practices
Work Arrangement
Remote (Worldwide)
