The Senior Data Analyst owns a business domain spanning Awayday's Operations, HR, Marketing, and Business Development, from the models at its foundation through to the reporting and analysis the business depends on. It is a deliberately broad mandate. You will build production-grade models against Awayday's conformed core and extend them into the semantic layer, develop the bespoke dashboards that sit atop them, conduct the ad hoc analysis stakeholders need, and help define the metrics that the departments within your domain rely on to make decisions day to day.
This role blends deep analytical rigor with genuine ownership. You will define what a metric means in partnership with the business, build and extend the models behind it, reconcile it to the source, and stand behind it with stakeholders, whether that work takes shape as a data model, a dashboard, or a one-off analysis. The ideal candidate is a proactive, results-oriented senior analyst, someone who pairs command of SQL and semantic modeling with sound data judgment and the communication skills to partner closely with the business.
Key Responsibilities:
Domain Ownership
- Own the Operations, HR, Marketing, and Business Development data domain end to end: modeling, delivery, reconciliation, and the stakeholder relationships behind it.
- Carry the domain's hardest analytical work, so it stops queuing behind a single central builder.
- Stay accountable for the health and accuracy of the domain's models and metrics, not only for their delivery.
- Extend the domain's models into the semantic layer as new measures and dimensions are required.
Metric Development and Reporting
- Help define and implement the KPIs and definitions Ops, HR, Marketing, and BD stakeholders rely on.
- Build and maintain reporting and dashboards, in our BI tools and in the semantic layer, for the domain's end users.
- Present insights and trends clearly, and conduct ad hoc analysis for stakeholders as needed.
Modeling and the Semantic Layer
- Build and extend the domain's models on top of the shared conformed core.
- Wire the domain's measures and dimensions into the semantic layer, so its metrics stay consistent with every other source.
- Write the tests, reconciliations, and documentation that make the models production-grade.
Standardization and Harmonization
- Own the standardization and harmonization within the domain, aligning definitions across brands so cross-brand metrics hold.
- Coordinate with local and central teams to write standardized definitions and data mappings across the portfolio.
Stakeholder Partnership and Delivery
- Partner with Ops, HR, Marketing, and Business Development stakeholders to define requirements and metrics before building them.
- Communicate project priorities and requirements to the tech lead, who assigns the work and runs peer review within the contract team, and coach the one to two contract analysts in your domain to grow their skills and the quality of their output over time.
- Run QA to confirm the domain's numbers reconcile before they reach our stakeholders.
AI and Analytics Enablement
- Curate the governed metrics and semantic definitions our AI assistant relies on, and validate its answers against the source.
Qualifications:
- 5+ years in data analysis, with demonstrated end-to-end ownership of an analytics area.
- Strong SQL and hands-on experience building models in a cloud data warehouse (Snowflake preferred) with a semantic modeling or transformation framework.
- Experience building reporting in a modern BI tool such as Domo, Looker, Tableau, or Power BI.
- A track record of translating business requirements into governed metrics and standing behind the numbers with stakeholders.
- Ownership of data quality and reconciliation for an area, and comfort directing others' work.
- Powerful oral and written communication skills to present findings to non-technical stakeholders and to distill the needs of our business teams.
- Practical, hands-on experience applying AI tools to real work, including LLM-assisted workflows. You know how to structure prompts and context and ground models on trusted data sources. Deep AI-engineering theory is not required, only fluency putting these tools to work.
- Openness to an evolving BI and semantic-layer stack, including evaluating tools beyond our current set as the platform matures.
Preferred Qualifications:
- Experience with a semantic or metrics layer and transformation tooling (dbt, MetricFlow, SQLMesh, or comparable).
- Subject-matter depth in Operations, HR, Marketing, or Business Development that you've supported as an analyst.
- Hospitality or vacation-rental domain experience.
- Familiarity with a CRM, marketing, or HRIS data source
Key Attributes:
- Strategic thinker with a proactive, problem-solving mindset.
- Strong attention to detail and a commitment to numbers that reconcile.
- Able to work independently and as part of a team, and to translate complex concepts into clear insight.
- Eager to learn and adapt in a fast-paced, acquisitive environment.
- An innate sense of curiosity and desire to help others.