Analytics Engineering Lead - Marketing Data & AI

RX Brasil; Amsterdam; On-site; EUR 49,000 - 82,000; Full time

Job summary

Elsevier is seeking an experienced analytics engineer to build trusted data foundations behind dashboards and AI products in Amsterdam. You will develop dbt models, semantic layers and data quality, while creating AI agents and a scalable evaluation framework for marketing insights.

You will collaborate with the Analytics Architect, Data Ops and marketers to define architecture, tests and release processes, ensuring reliable, explainable results across teams.

Qualifications

• 3+ years of experience building and running production data and analytics systems, with strong SQL and Python.
• Solid dbt experience, including modelling, testing, macros and ideally a semantic or metric layer.
• You’ve designed models others rely on.

Responsibilities

• Design and build the dbt models and semantic layer behind our dashboards and AI products, with clear standards, tests, lineage and documentation, so marketers can trust the numbers.
• Build and run AI agents for marketing on Snowflake, our dbt semantic layer, MCP connections and LLM tools, and help define the architecture roadmap.
• Create a simple, strong evaluation approach: standard question sets with expected answers, regression checks before each release, and open reporting on accuracy.
• Set up and maintain our user acceptance testing (UAT) environment and a repeatable path to production.
• Work with Data Ops on platform and engineering standards, and with marketers to understand the decisions they need to make.
• Document as you build, so our systems are easy to maintain and knowledge is shared across the team.

Skills

SQL

Python

dbt

Semantic layer

LLMs

CI/CD

Testing

Documentation

Data quality

Snowflake

Tools

Snowflake

MCP

Tableau

Salesforce

Adobe Analytics

Braze

Sprinklr

Job description

Elsevier is seeking an experienced analytics engineer to build trusted data foundations behind dashboards and AI products in Amsterdam. You will develop dbt models, semantic layers and data quality, while creating AI agents and a scalable evaluation framework for marketing insights.

You will collaborate with the Analytics Architect, Data Ops and marketers to define architecture, tests and release processes, ensuring reliable, explainable results across teams.