Manager, Reporting & Analytics

Posted 4 Days Ago
Be an Early Applicant
2 Locations
In-Office or Remote
49K-82K Annually
Mid level
Artificial Intelligence • Healthtech • Information Technology • Other • Analytics
The Role
Build and maintain dbt models, semantic layers, data quality systems, and AI agents supporting marketing dashboards and decision-making. Develop evaluation frameworks, UAT environments, and production release processes for AI products. Partner with marketers, Data Ops, and technology teams to translate business questions into reliable data solutions, while documenting systems and maintaining engineering standards.
Summary Generated by Built In

Are you excited to build trusted data foundations that power marketing dashboards and AI products?


Would you like to combine analytics engineering and AI to help marketers make better-informed decisions?


About Team:

Marketing Performance is a collaborative team that measures the impact of marketing across our Academic, Government and Corporate Markets. We define what to measure, show how marketing contributes to business results, and help leaders decide what to do next. We've built a trusted semantic layer and an AI agent for marketing performance, and we're expanding both. We share ideas and ownership, and increasingly deliver insights through AI products as well as dashboards.


About the role

You'll build the trusted data foundations behind our dashboards and AI products: the dbt models, metric definitions and data quality that make them reliable. You'll also build AI products that help marketers and leaders make better decisions, including an agent that drafts monthly performance commentary.

You'll work in a small, agile team, alongside our Analytics Architect and reporting to the Director of Marketing Performance. You'll partner closely with marketers, Data Ops and technology colleagues, and you'll help shape how we build, test and release. This is a role for someone who wants to understand marketing as well as engineer for it.


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.

What you'll bring

  • 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.
  • Good dimensional modelling fundamentals, such as grain, conformed dimensions and slowly changing dimensions.
  • Hands-on experience building with LLMs (agents, tool or function calling, retrieval), ideally in production, and a real interest in how to measure and improve answer quality.
  • Solid engineering habits: version control, testing, code review, CI and documentation.
  • The ability to build relationships across teams and earn trust. Your work makes a difference when people use it.
  • Skill at translating in both directions: explaining technical answers in plain language, and turning broad marketing questions into answerable ones.

What will help you thrive

  • Curiosity and a willingness to experiment. You keep up with what's changing, try things yourself and form your own views.
  • Good judgement about when to change course, and the confidence to say when something isn't working.
  • A commercial understanding of marketing. Experience in either B2B or B2C is welcome, along with curiosity about the other.

Nice to have

Experience with Snowflake, MCP, Tableau, identity resolution across sources, marketing attribution, B2B funnel measurement, or marketing data sources such as Salesforce, Adobe Analytics, Braze and Sprinklr.


Work in a Way That Works for You

We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.


Working Pattern

Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.


About the Business

A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world. Are you excited to build trusted data foundations that power marketing dashboards and AI products?


Primary Location Base Pay Range: NLD Amsterdam (Radarweg) €49,000 - €81,700. This role is covered by the Collective Labor Agreement Publishing Industry.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.

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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.

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Skills Required

  • 3+ years of experience building and running production data and analytics systems
  • Strong SQL and Python skills
  • Solid dbt experience, including modeling, testing, macros, and ideally a semantic or metric layer
  • Experience with dimensional modeling, including grain, conformed dimensions, and slowly changing dimensions
  • Hands-on experience building with LLMs, including agents, tool or function calling, or retrieval
  • Experience measuring and improving AI answer quality
  • Experience with version control, testing, code review, CI, and documentation
  • Ability to build relationships across teams and earn trust
  • Ability to explain technical concepts in plain language and translate marketing questions into answerable problems
  • Curiosity and willingness to experiment with evolving technologies
  • Good judgment and confidence to identify when approaches are not working
  • Commercial understanding of marketing
  • Experience with B2B or B2C marketing
  • Experience with Snowflake, MCP, Tableau, identity resolution, marketing attribution, B2B funnel measurement, Salesforce, Adobe Analytics, Braze, or Sprinklr

Elsevier Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Elsevier and has not been reviewed or approved by Elsevier.

  • Leave & Time Off Breadth — Feedback suggests paid time off spans vacation, holidays, sick days, bereavement, military leave, and volunteer time. Family-related leave options are also emphasized as part of the package.
  • Healthcare Strength — Feedback suggests medical, dental, vision, life insurance, wellness initiatives, and an EAP form a comprehensive health offering. Gym support and wellbeing hubs reinforce an ongoing health and wellness focus.
  • Retirement Support — Feedback suggests retirement programs include a 401(k)/retirement plan and pension options, with long-term savings vehicles such as an employee stock purchase plan also available. These elements contribute to a sense of financial security beyond base pay.

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The Company
HQ: Amsterdam
Year Founded: 1880

What We Do

Elsevier is a world-leading provider of information solutions that enhance the performance of science, health, and technology professionals, empowering them to make better decisions, and deliver better care. Because informed decisions lead to better outcomes, Elsevier is a leader in information and analytics for customers across the global research and health ecosystems. Elsevier helps researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. We do this by facilitating insights and critical decision-making for customers across the global research and health ecosystems.

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