About the role
As a Senior Data Analyst on Elsevier’s Global Business Intelligence team, you will help the Sales organization work more effectively by turning data into insights that sales representatives, sales leaders, and senior management can act on.
The work suits someone who pairs strong analytical and technical skills with real business understanding, and who instinctively takes a process or problem apart to look for a better way to solve it.
We work on current technology and expect you to use it. Our warehouse is moving to Snowflake, and modern AI tools — Claude, Claude Code, ChatGPT, and Codex — are part of how this team works every day, not an optional extra.
You do not need to arrive knowing all of it. We are looking for strong analytical judgment and a real appetite to learn these tools rather than a checklist of them — where you start will shape how quickly you take things on, not whether you are right for the role. Onboarding is deliberately staged: you will build understanding of our data and models alongside the team first, and hands-on access to our warehouse environment follows once you are ready to work in it confidently.
Accountabilities
- Partner with stakeholders to understand their business processes and challenges, and propose how data can help.
- Define clear specifications, then design and build user-friendly dashboards and visualizations in Excel, Salesforce, and Tableau that deliver actionable insight.
- Design, build, and maintain Nexus, our data warehouse, together with the rest of the team — including the SQL and transformation logic behind it. We are migrating from SQL Server to Snowflake, and you will help shape how we build on it.
- Take the lead on ambiguous or high-visibility requests: scope what is worth building, push back where data will not answer the question being asked, and bring a recommendation to senior stakeholders.
- Set and uphold standards for how the team builds — data modeling conventions, code review for SQL and data models, and consistency across dashboards.
- Use AI tooling — Claude, Claude Code, ChatGPT, and Codex — to accelerate development, analysis, and documentation, and set the standard for how the team uses it responsibly.
- Review our reporting portfolio for improvements and unmet reporting needs, run ad hoc analyses and presentations as they arise, and improve the sales tools our colleagues rely on — training users so that adoption and institutional knowledge grow with them.
- Work across our international organization — Finance, Operations, Sales, Content, and IT — to keep our data aligned, reliable, and current.
- Share best practices with analysts, data governance specialists, and technical experts across the wider Elsevier Data & Analytics community.
What success looks like
- In your first three months: you know the Nexus data model, the reporting portfolio, and the stakeholders behind it, and you are contributing changes with support from the team.
- By six months: you are working confidently across our warehouse and reporting environment, and stakeholders come to you with their reporting questions.
- By twelve months: you are influencing how the team builds — SQL and data modeling conventions, dashboard design — and reporting that used to take days is faster or self-serve.
Qualifications
- 5+ years in a business intelligence or data analyst role.
- Strong SQL skills and experience working in a data warehouse — Snowflake ideally — including window functions, CTEs, and query optimization against large tables.
- Experience building and testing data transformation models — in any modern framework — or strong SQL and a clear appetite to learn one.
- Experience building reports and dashboards in a visualization platform such as Tableau or Power BI.
- Advanced Microsoft Excel skills.
- Hands-on experience with AI tools — Claude, Claude Code, ChatGPT, or Codex — or a clear appetite to work this way day to day, with the judgment to know when to trust output and when to verify it.
- Experience setting technical standards or reviewing others’ work, and comfort leading requests where the right answer isn’t defined upfront.
- A track record of translating stakeholder questions into analysis, and presenting findings clearly to non-technical audiences.
- Strong organizational skills, with the ability to work independently and prioritize across competing requests.
Nice to have
- A degree in business, accounting, finance, computer science, statistics, or a related field.
- T-SQL, or experience with a Microsoft SQL Server environment.
- ETL and orchestration tooling such as Talend, Fivetran, or Airflow.
- Experience with quantitative and qualitative research methods or customer insight work.
Why join us
Global Business Intelligence is a small, senior team with direct reach into the Sales organization — your work is used by representatives and leadership rather than filed away. You will join at the point where the platform is being rebuilt, so the decisions you make now set the standard for years.
- A modern stack — Snowflake and current AI tooling — with budget and mandate to keep it current.
- Visible, senior-facing work: your analysis reaches sales leadership and senior management directly.







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