för 9 månader sedan
SingaporeHybridför 9 månader sedan
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Teamtailor is a global Employer Branding and ATS SaaS platform used by over 13,000 companies, 250,000 users, and available in 90 countries worldwide. 🌍
Working at Teamtailor means being part of a dynamic, fast-paced tech company that values impact and responsibility. Our workplace fosters an environment where everyone can contribute meaningfully to the growth of the company. 🎉🥳
We are now looking for a Director - Data & Analytics to join our team, based in Stockholm
This role will own Teamtailor's data strategy and infrastructure: the pipelines, architecture, and governance that everything else runs on. This role builds and maintains a scalable, reliable, well-documented data foundation, and defines the semantic layer and metric definitions that keep numbers consistent across the business. Business intelligence and reporting are owned by the teams closest to the decisions, primarily Revenue Operations and FP&A, who build on top of the foundation this role provides.
Define and own Teamtailor's data strategy, architecture roadmap, and infrastructure investment priorities.
Build and lead the Data Engineering team, including defining ways of working for the data team, balancing priorities, and driving a proactive approach.
Establish a data governance model covering reliability, data quality, access control, and privacy/compliance (GDPR and equivalent).
Act as thought partner to the Leadership team on data infrastructure and its commercial implications.
Develop a unified KPI and metric framework across revenue, product, customer success, marketing, and operations.
Partner with business leaders to understand strategic and operational requirements, translating them into data models and analytical capabilities.
Ensure that business-critical insights are accurate, timely, and accessible to decision-makers.
Own and evolve the data architecture: ingestion, transformation, and a layered data model (staging, integration, semantic layers, marts).
Ensure pipelines are reliable, observable, well-documented, and scale with the business.
Own the semantic/metrics layer: define and maintain a single source of truth for core metric definitions so that RevOps, FP&A, and other teams report consistent numbers even when building their own dashboards.
Manage BI platform infrastructure (e.g., Looker, Metabase) at the tooling and access level, without owning dashboard content.
Partner with RevOps and FP&A as the primary owners of BI, reporting, and dashboards, ensuring they have clean, well-modeled, self-serve-ready data.
Set and enforce standards for how business teams build on the data foundation (naming, definitions, governance) to prevent metric drift.
Provide training and support to embed a self-serve data culture across business teams.
Support RevOps on the data infrastructure behind GTM and revenue analytics.
Support FP&A on data infrastructure for forecasting, budgeting, and board-level reporting.
Work with Product and Engineering on data infrastructure for product analytics and instrumentation.
Support Marketing and CS with modeled, reliable underlying data as needed.
Proven ability to understand business needs, ask the right questions, and translate them into actionable data solutions.
Experience building KPI frameworks and metric definitions across complex SaaS environments.
Strong communication skills and ability to work with executive stakeholders.
Strong track record building and scaling modern data architecture (ingestion, transformation, orchestration).
Hands-on experience with BigQuery, Snowflake, or similar platforms; comfortable reviewing pipeline and modeling work directly, not just managing it.
Experience with layered data modeling, semantic/metrics layers, and transformation frameworks (e.g., dbt).
Strong grasp of data governance, documentation, observability, and data quality practices.
Working familiarity with BI tools (Looker, Metabase) sufficient to support other teams, not to build reporting.
Experience leading Data Engineering teams (3+ people).
Ability to set direction, coach technical teams, and scale a data function.
Experience in a global SaaS company in a strong growth phase.
Deep technical skills in addition to a strong commercial understanding.
Experience building a data warehouse bottom up
Familiarity with operational analytics, revenue analytics, or product analytics.
Experience embedding self-serve data culture in scaling organizations.
If this sounds like you, please APPLY!