Nimble Gravity
Nimble Gravity
51 – 200 Employees
ConsultingLogisticsMarketing
Nimble Gravity is a consulting, marketing, and logistics company that helps businesses apply artificial intelligence, data science, and digital technologies to practical growth challenges. Its services include predictive and prescriptive analytics, digital transformation, software engineering, e-commerce strategy, and CRM optimization, including Salesforce-focused solutions. Nimble Gravity also develops generative AI agents and data-driven commerce tools designed to support automation, improve decision-making, and advance digital transformation initiatives.

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.

Description

  • 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

Requirements

  • 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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