Our client, a rapidly growing SaaS company, is seeking a Senior Analytics Engineer to lead the design and development of scalable data pipelines, semantic data models, and insightful dashboards. The goal is to empower business teams with high-quality, self-service analytics and data-driven insights to support strategic decision-making across the organization.
This is a hands-on, cross-functional role at the intersection of data engineering, business intelligence, and analytics strategy. The ideal candidate will have a strong command of Power BI, DAX, SQL, and modern ELT practices.
Senior Analytics Engineer (Power BI / Data Modelling / ELT Pipelines)
Your responsibilities
- Lead the end-to-end ELT process: extract data from various sources (e.g., Salesforce, HubSpot, Recurly, Stripe, Mixpanel, Azure SQL) and transform it into reusable models within Power BI.
- Design and manage automated data pipelines supporting scalable, cross-functional reporting needs.
- Implement and enforce best practices for data transformation using Power Query (M) and DAX.
- Develop and maintain semantic models in Power BI to support self-service analytics and standardized reporting.
- Build visually compelling, intuitive dashboards presenting key business metrics such as revenue, product usage, retention, and customer engagement.
- Continuously optimize dashboard performance and usability.
- Collaborate closely with teams across Sales, Product, Marketing, Support, Operations, and Finance.
- Translate business requirements into analytical solutions and communicate complex data in a clear, actionable manner.
- Apply Power BI governance best practices (workspace architecture, row-level security, access control).
- Maintain documentation for data definitions, transformation logic, and dashboard usage.
- Provide training and support to non-technical users to encourage data literacy and self-service reporting.
Our requirements
- Minimum 5 years of experience in a data analytics or BI engineering role.
- Proven experience building ELT pipelines using Power BI or equivalent tools (e.g., SQL pipelines, Azure Data Factory).
- Expert-level proficiency in: Power BI Desktop & Power BI Service DAX and Power Query (M language) SQL Data modelling and semantic layer design
- Experience working in a SaaS environment with KPIs such as MRR, ARR, churn, CAC, CLTV.
- Strong analytical thinking, attention to detail, and ability to balance technical depth with business context.
- Ability to integrate data from multiple sources, including APIs, databases, and cloud platforms.
- Excellent communication and stakeholder management skills.
- Experience enabling or mentoring non-technical stakeholders in dashboard usage and interpretation.
- Familiarity with Microsoft Power Platform (e.g., Power Automate, Power Apps).
- Background in fast-paced SaaS or scale-up environments.