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.
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.
requirements-expected :
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.
