[Hiring] Analytics Engineer @Prolific

Role Description

As an Analytics Engineer in the Data Infrastructure Team at Prolific, you’ll be at the forefront of transforming and maintaining Prolific’s data infrastructure as the way people work with data changes rapidly. Your work will be instrumental in redesigning and scaling our data stack, ensuring data pipelines are robust, efficient, and reliable, and that our data is ready to be queried by people and AI systems alike.

By owning and optimising our analytics codebase and semantic layer, you’ll empower teams across the business to get trustworthy answers, whether through BI dashboards or natural language questions. You’ll help shape how we bring LLMs and agents into analytics engineering safely and effectively, and you’ll bridge the gap between technical and non-technical stakeholders so that complex data solutions are clearly understood and aligned with business goals.

Qualifications

• Deep experience with dbt and SQL to design, build, and maintain scalable data models.
• Experience defining metrics, entities, and business logic in a semantic layer (e.g. dbt Semantic Layer/MetricFlow, Cube, LookML or similar).
• Hands-on experience using LLMs in data work, such as classification, extraction, or enrichment within transformations.
• Familiarity with AI coding assistants and agents (e.g. Claude Code, Cursor, MCP-based tooling).
• Strong familiarity with cloud platforms such as AWS or GCP.
• Passion for ensuring high data quality through tests, assertions, evaluations, and robust documentation.
• Ability to understand business needs and communicate effectively with non-technical stakeholders.
• Skilled at working cross functionally and translating complex technical concepts into actionable insights for the business.
• Proficiency in designing repeatable, scalable workflows for data transformation.

Requirements

• Create complex dbt models, custom macros, and reusable packages.
• Design and maintain a semantic layer with well-defined metrics, dimensions, and descriptions.
• Build and productionise LLM-powered steps within our pipelines.
• Design and adopt agentic workflows across the analytics engineering lifecycle.
• Monitor and maintain dbt workflow jobs, ensuring smooth data refreshes and up-to-date pipelines.
• Write tests and assertions to validate data integrity and consistency across models.
• Create and maintain thorough documentation of dbt processes and semantic definitions.
• Act as a key communicator, translating technical data issues into understandable business terms.
• Support junior analysts and data engineers in setting up experimentation platforms.
• Work closely with product, engineering, and BI teams to ensure data infrastructure supports evolving business needs.

Benefits

• Competitive salary.
• Remote working opportunities.
• Access to a unique human data platform.
• Opportunities for groundbreaking research.
• Impactful, mission-driven culture.