Data Engineer
Indexed description
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.
We are seeking a senior individual contributor who can take ownership of the analytics and AI technology stack, operate independently, and act as a trusted partner to stakeholders across the business. This is not a people management role; instead, it requires someone who enjoys balancing hands-on technical delivery with collaboration, influencing, and guiding others. The ideal candidate will be equally comfortable writing code, solving complex technical challenges, and engaging with colleagues to understand business needs and drive impactful outcomes.
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
- 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, metrics, and KPI definitions
- Build and maintain semantic layers within Snowflake
- Monitor model performance, accuracy, and cost usage
- Implement safeguards to ensure reliable and explainable outputs
- Maintain governance standards for AI-enabled analytics workflows
- Strong 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
- 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
- Hybrid working - 2 days a week in the London office
- Wellbeing: Sanctus Coaching, Virtual fitness sessions, Wellbeing webinars, Annual Wellbeing day
- Subsidised Gym Membership
- Private Medical Insurance (including Dental and Vision) and Life Assurance
- 25 days holiday (increasing to 30 days at a rate of 1 extra day per year)
- Employer pension contribution of 5% of your gross salary, if you contribute a minimum of 3%
- Season ticket Loan
- Cycle to Work Scheme
- Annual Discretionary Bonus
Create a free Caio profile to unlock more results and save your role and location preferences.
Unlock free search