Senior Data Analyst (#4451)

N-iX is a global software development company founded in 2002, connecting over 2,400+ tech professionals across 40+ countries. We deliver innovative technology solutions in cloud computing, data analytics, AI, embedded software, IoT, and more to global industry leaders and Fortune 500 companies. Join us to create technology that drives real change for businesses and people across the world.

Our customer is the European online car market with over 30 million monthly users, with a market presence in 18 countries. As a Senior Data Analyst, you’ll join our clients’ Sales Analytics Team and act as a key analytical partner for the sales, revenue, and commercial strategy teams. You will help shape business decisions by grounding them in data, building self-service analytics tools, and generating insights that improve sales performance, customer engagement, and revenue growth.

Responsibilities:

• Data-Driven Sales Performance Optimization: as a Data Analyst, you play a key role as an analytical sparring partner for our customers’ sales organization, ensuring that commercial decisions and sales processes are grounded in robust data. You will be an integral part of our customers’ Sales Analytics Team.
• Deep Customer & Sales Funnel Understanding: you will develop a deep understanding of the customer segments, sales funnels, and commercial products. You will analyze the acquisition, channels, sales pipeline conversion, account health, churn, and upsell behavior to identify improvement opportunities for sales teams across markets.
• Data Enablement & Self-Service Analytics: you build self-service analytics products such as dashboards, forecasting models, and metric frameworks. You evaluate new analytics technologies, including GenAI applications, and establish scalable use cases that give sales teams and leadership easy access to reliable insights. You empower stakeholders by enhancing their data literacy and enabling data-and insights-driven decision-making.
• Consultative Analytics & Insight Generation: you answer commercial and operational questions through deep-dive analyses, clearly communicating insights, trends, and recommendations to sales, operations, and leadership teams. You help transform complex analysis into actionable guidance that supports revenue growth, customer success, and sales efficiency.
• Collaboration & Data Quality: you collaborate with CRM, engineering, tracking, and data platform teams to ensure high-quality data instrumentation, data reliability, and alignment on metric definitions. You help maintain documentation for commercial KPIs and contribute to building a shared understanding of sales performance drivers.
• Experimentation & Optimization: you support experimentation and optimization initiatives by designing A/B or quasi-experimental tests, defining hypotheses, ensuring statistical rigor, and interpreting outcomes to drive improvements across sales processes, pricing strategies, and sales enablement tools.

Requirements: 

• 4+  years of experience in analytics, sales operations, revenue insights, or data-driven consulting.
• Be able to work within Canadian Timezone (EDT).
• Excellent SQL skills: you are comfortable querying large datasets and optimizing queries for performance.
• Experience with Python for data analysis, automation, or forecasting.
• Ability to model data and build efficient analytics pipelines for production or stakeholder-facing use cases.
• Strong statistical knowledge, including experiment design and evaluation.
• Expertise in BI tools such as QuickSight, Tableau, or similar platforms, including building semantic models, cubes, and automated reports.
• Strong communication skills - you can explain insights, trends, and analytical solutions to technical and non-technical stakeholders.
• High motivation, proactiveness, and a genuine enthusiasm for transforming sales performance through data.
• Upper-Intermediate of English, both spoken and written  

Would be a plus:

• Experience with cloud-based data lakes or data warehouses (e.g., Redshift, BigQuery, Snowflake) and analytics engineering tools (e.g., dbt).
• Familiarity with CRM systems (e.g., Salesforce) and sales performance tracking.