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Nimble Gravity
Nimble Gravity
51 – 200 Angajați
ConsultanțăLogisticăMarketing
Nimble Gravity este o companie de consultanță, marketing și logistică ce ajută întreprinderile să aplice inteligența artificială, știința datelor și tehnologiile digitale pentru a aborda provocările practice ale creșterii. Serviciile sale includ analize predictive și prescriptive, transformare digitală, inginerie software, strategie de comerț electronic și optimizarea CRM, inclusiv soluții axate pe Salesforce. Nimble Gravity dezvoltă, de asemenea, agenți de inteligență artificială generativă și instrumente de comerț bazate pe date, concepute pentru a sprijini automatizarea, a îmbunătăți procesul decizional și a impulsiona inițiativele de transformare digitală.
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Locurile de muncă ale companiei

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.

USStatele Unite ale AmericiiRemoteNormă întreagăSeniorLiderLimbă Obligatorie: englezăInginer de analiză a datelor
AirflowERPPythonSQL

Descriere

  • 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

Cerințe

  • 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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