Senior Analytics Engineer
Employment Info
JOB DETAILS
Requirements
- 5+ years in analytics engineering, data analytics or BI, ideally in B2B SaaS
- Advanced SQL and dbt. You write clean, well tested transformation logic and understand the difference between a loose set of dbt models and a true, well layered set of marts or semantic layer
- Strong dimensional modelling instincts. You know when to apply Kimball or star schemas, SCD2, or a simpler normalised approach. You model state over time correctly and care about making data trustworthy and interpretable, not just queryable
- Snowflake as a primary warehouse (or equivalent cloud warehouse)
- Analyst instincts. You can frame an ambiguous business question, run the analysis and tell the story, not just build the pipeline
- BI tool expertise. You think about the end user when you design a dashboard
- Fluency with AI tools. You use tools like Claude Code, Cursor or Copilot as part of your daily workflow, with the judgement to verify what they produce
- Exceptional communication. You translate complex data into clear, actionable narratives for business leads and executives alike
- A bias for proactivity. You spot questions before others do, follow through with rigour and care about the downstream business impact of your work
Responsibilities
- Owning analytics for business operations. Partnering closely with teams like Finance and Customer Success to understand their most important questions, then delivering reliable, timely insight on revenue, ARR, churn, retention, customer health and engagement
- Building and maintaining data models in dbt. Designing clean, well tested transformation logic on Snowflake that powers reporting across the business, from subscription and billing data through to customer usage patterns
- Modelling business data correctly. Building dimensional and slowly changing dimension (SCD2) models so that revenue and churn metrics are point in time accurate, not just current state snapshots
- Building self service data products. Trusted dashboards and well documented marts that give business teams instant, accurate access to the metrics they rely on, reducing ad hoc requests
- Acting as a data quality champion. Owning accuracy, reliability and testing across your domains, and working with our Senior Data Engineer to ensure clean data flows from source systems (HubSpot, Subskribe, Vitally and our product database)
- Proactively surfacing insight. Spotting trends, anomalies and opportunities before they’re asked for, and presenting clear recommendations to senior stakeholders
- Setting standards. Translating ambiguous business problems into well modelled, trustworthy data, establishing robust analytics engineering practices and mentoring others as our data capability grows
Desired Qualifications
- Nice to have: Experience partnering directly with business operations teams such as Finance or Customer Success. You understand the metrics and data they actually need to do their jobs
- Nice to have: Familiarity with our source systems: HubSpot, Subskribe, Vitally
- Nice to have: Experience building or contributing to a semantic or metrics layer
- Nice to have: BI tooling such as Sigma (or Looker, Mode or similar)
- Nice to have: Python or R for more complex analysis or automation
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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