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Senior Data and Analytics Engineer United States Remote
Build Snowflake data models, pipelines, and semantic layers for Nimble Gravity’s financial-institution clients. Help deliver reliable AI agents and measurable outcomes through client-facing technical work.
विवरण
- Design flexible, high-performance data models that establish trusted sources of truth across business domains
- Build and maintain SQL, Python, dbt, and Snowflake infrastructure for reporting, analysis, and automation
- Validate Snowflake data quality and create automated tests for data models
- Contribute to governance practices covering permissions, lineage, and business definitions
- Implement access controls that restrict models to authorized data
- Create semantic models that make line-of-business data available to natural-language queries through Cortex Analyst
- Define and verify the metrics, dimensions, and relationships required by AI agents
- Find and correct structural, naming, and coverage issues that may produce agent errors or unreliable answers
- Maintain playbooks, reusable modeling templates, and libraries of semantic models
- Lead technical workshops that strengthen team capabilities
- Create semantic-view configurations and YAML or Markdown skill files for non-technical analysts
- Manage the data stack from source ingestion through the semantic layer, with a focus on reliable, maintainable production systems
- Partner with clients, engineers, and AI specialists to convert emerging technology into measurable business results
- Monitor post-launch adoption, address points of friction, and continue engagement until the data product is dependable and transferred to operational teams
- Convert business needs into technical specifications and deliver practical feedback to leadership
आवश्यकताएँ
- At least eight years in analytics engineering, data engineering, or a related technical field, including some customer-facing or cross-functional work
- Use an AI coding assistant as a primary development tool every day
- Write advanced SQL, including window functions and complex joins, independently
- Professional experience with dbt
- Delivered a production data model or pipeline used by non-technical business stakeholders
- Comfortable using Git for branches, pull requests, and code reviews
- Proven ability to turn business requirements into clear technical specifications
- Strong command of CTEs, window functions, and incremental pipeline design
- Experience developing data infrastructure for large relational datasets
- Built and maintained dbt projects with testing, documentation, and CI/CD
- Write modern, type-hinted, maintainable Python for data pipelines and automation
- Regularly use an LLM coding assistant such as CoCo, Cursor, GitHub Copilot, Claude, or an equivalent tool
- Able to create semantic-view configurations or structured skill files that capture edge cases and domain knowledge
- Effective communication in client-facing settings
- Knowledge of Snowflake Cortex products, including Cortex Analyst, Cortex Agents, Cortex Search, semantic views, and Dynamic Tables
- Experience with Airflow or another orchestration framework is a strong advantage
- Familiarity with enterprise systems such as ERP, CRM, or HRIS is a strong advantage
- Eligible to work without H1B visa sponsorship
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