Orgvue
Computer Software
Data&InsightEngineer
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“Data & Insight Engineer at Orgvue. Skills: Data pipeline engineering, AI Insight Pipeline Development, Semantic Data Modelling. Build and own an AI-native analytics environment. Build and maintain robust data ingestion and transformation pipelines”
What You'll Achieve.
Generate insights automatically from data rather than manually through dashboards and reports; Support conversational analytics and AI-driven business intelligence
Industry & Context.
Translating business questions into analytical models and metrics
What They're Looking For.
Must Have
SQL and data modelling expertise, Experience working with Snowflake, Experience with analytics engineering tools such as dbt, Proficiency with Python or similar languages for data workflows, Experience building and maintaining data pipelines, Experience translating business questions into analytical models and metrics, Experience working with analysts, product teams, and business stakeholders to support decision-making
Nice to Have
Experience working with large language models (LLMs) or AI-enabled analytics platforms, Familiarity with prompt design or AI-assisted analytical workflows, Familiarity with Snowflake Intelligence
What You'll Do.
Build and own an AI-native analytics environment
Build and maintain robust data ingestion and transformation pipelines
Integrate data from operational systems into the analytics platform
Maintain data quality frameworks and validation checks
Optimise performance of data processing and analytics workloads
Automate recurring analysis traditionally performed manually
Enable natural-language analytics across curated datasets
Develop systems that translate business questions into structured data queries
Design and maintain curated business data models that support reliable analytics and AI-driven insights
Define core business entities
Build and maintain semantic layers within Snowflake
Monitor model performance
Implement safeguards to ensure reliable and explainable outputs
Maintain governance standards for AI-enabled analytics workflows
How You'll Work.
Team & Collaboration
Working with analysts, product teams, and business stakeholders to support decision-making
Full Job Description
Orgvue is an organizational design and planning platform that empowers businesses to transform their workforce by understanding the work people do and the skills they have. Our platform connects strategy to structure, providing clarity of vision, so leaders can build a more adaptable, better performing organization that thrives in a constantly changing world of work. The world’s largest and best-known enterprises and consulting firms use Orgvue to visualize and model current and future states of the organization and make faster, more informed decisions. The company is headquartered in London, with offices in Philadelphia, The Hague, Toronto, and Sydney. **Role Overview** The Data & Insight Engineer will build and own an AI-native analytics environment where insights are generated automatically from data rather than manually through dashboards and reports. This role combines data engineering, analytics engineering, and AI-enabled insight generation. Responsibilities include building semantic data models, developing automated insight pipelines, and integrating Snowflake Cortex capabilities to support conversational analytics and AI-driven business intelligence. **Responsibilities** **Data Pipeline Engineering** * Build and maintain robust data ingestion and transformation pipelines * Integrate data from operational systems into the analytics platform * Maintain data quality frameworks and validation checks * Optimise performance of data processing and analytics workloads **AI Insight Pipeline Development and ownership** * Automate recurring analysis traditionally performed manually * Enable natural-language analytics across curated datasets * Develop systems that translate business questions into structured data queries **Semantic Data Modelling** * Design and maintain curated business data models that support reliable analytics and AI-driven insights * Define core business entities, metrics, and KPI definitions * Build and maintain semantic layers within Snowflake **
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