Data and Analytics Engineer

Job not on LinkedIn

🔥 4 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

📊 Analytics Engineer

👻 Ghost score 15%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Nimble Gravity

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Nimble Gravity is a company specializing in AI acceleration and automation services, leveraging cutting-edge data science, generative AI, and digital technologies to transform business challenges into growth opportunities. They provide a comprehensive suite of services, including predictive and prescriptive analytics, digital transformation strategies, software engineering, e-commerce solutions, and CRM optimization, particularly using Salesforce. Nimble Gravity is known for creating AI-powered solutions such as automated generative AI agents and data-driven e-commerce strategies, helping businesses accelerate their digital transformation and improve decision making.

📋 Description

• Architect flexible, performant data models driving LOB teams toward single sources of truth across business domains • Use SQL, Python, dbt, and Snowflake to build and maintain data infrastructure for reporting, analysis, and automation • Perform data QA and develop automated testing procedures for Snowflake data models • Provide input into data governance strategies, including permissions, data lineage, and data definitions • Design data security so models only access authorized data • Build semantic data models exposing LOB data to natural-language queries via Cortex Analyst • Define and validate metrics, dimensions, and relationships for AI agents • Identify and resolve data structure, naming, and coverage gaps that could cause agent failures or incorrect results • Document playbooks, reusable data model templates, and semantic model libraries • Run technical workshops to upskill team members • Author semantic view configurations and YAML/Markdown skill files for non-technical analysts • Own the full data stack from source ingestion to semantic layer, ensuring production reliability and maintainability • Work directly with clients, engineers, and AI specialists to turn emerging technology into measurable business outcomes • Track adoption after go-live, identify stall points, and re-engage until the data product is reliable and handed over to run teams • Translate business requirements into technical specifications and provide actionable feedback to leaders

🎯 Requirements

• 8+ years of experience in analytics engineering, data engineering, or a related technical role, with at least a portion of it customer-facing or cross-functional • Daily use of an AI coding assistant as a primary development tool • Proficient in SQL; can write window functions and complex joins without referencing documentation • Experience with dbt • Has shipped production data model or pipeline that non-technical business users actually relied on • Comfortable in Git (PRs, branches, code review) • Demonstrable experience translating business requirements into technical specifications • Advanced SQL: CTEs, window functions, incremental pipeline patterns • Experience building data infrastructure involving large-scale relational datasets • Experience building and maintaining dbt projects with testing, documentation, and CI/CD pipelines • Modern, type-hinted, readable Python; understanding of Python-based data pipelines and automation workflows • Daily use of an LLM coding assistant such as CoCo, Cursor, GitHub Copilot, Claude, or equivalent • Ability to write semantic view configurations or structured skill files handling edge cases and domain knowledge • Client-facing communication skills • Knowledge of Snowflake Cortex, including Cortex Analyst, Cortex Agents, Cortex Search, semantic views, and Dynamic Tables • Experience with Airflow or other orchestration frameworks is a strong plus • Familiarity with enterprise business systems such as ERP, CRM, or HRIS is a strong plus • Must be eligible to work without H1B visa sponsorship