Senior Analytics Engineer – AI/BI

<p>Rithum™ is the world’s most trusted commerce network, accelerating how brands, suppliers, and retailers work together to deliver seamless e-commerce experiences. We provide an unmatched platform for brands and retailers, enabling them to accelerate growth, optimise operations across channels, scale product offerings and enhance margins.</p> <p>Today, more than 40,000 companies trust Rithum to grow their business across hundreds of channels, representing over $50 billion in annual GMV. Using our commerce, marketing, and delivery solutions, our customers create optimised consumer shopping journeys from beginning to end.</p> <p> </p> <p><strong>Overview </strong></p> <p>As a Senior BI Engineer, you architect next-generation business intelligence solutions that combine traditional analytics with AI-powered insights to drive autonomous decision-making across the organization. You lead the transformation toward intelligent, self-service analytics platforms while leveraging generative AI, machine learning, and automated data discovery tools to deliver predictive and prescriptive business insights. This role requires expertise in both traditional BI foundations and emerging AI-assisted analytics technologies. </p> <p><em> </em></p> <p><strong>Responsibilities</strong></p> <ul> <li>Design and maintain intelligent dashboards, automated reports, and self-service analytics platforms using Looker (LookML), Power BI, and emerging AI-native BI tools.</li> <li>Build and optimize real-time data models, ETL/ELT pipelines, and streaming analytics architectures to support scalable reporting and analytics.</li> <li>Implement automated data quality monitoring, anomaly detection, and intelligent alerting systems to ensure reliable insights.</li> <li>Integrate large language models (LLMs) and generative AI tools to enable natural language querying and automated insight generation.</li> <li>Develop predictive models, recommendation engines, and forecasting systems embedded within BI workflows.</li> <li>Leverage AI coding assistants (e.g., GitHub Copilot, Cursor) for rapid development, automated testing, and intelligent code optimization.</li> <li>Apply core programming principles to build scalable, maintainable analytics solutions, including modular code design and version-controlled development workflows.</li> <li>Collaborate with cross-functional teams to identify opportunities for AI-enhanced decision-making and autonomous business processes.</li> <li>Lead the transition from static reporting to dynamic, AI-driven analytics while mentoring junior engineers in modern BI and AI methodologies.</li> <li>Adapt quickly to changing business needs, priorities, and technologies.</li> </ul> <p> </p> <p><strong>Qualifications  </strong></p> <p>Minimum Qualifications  </p> <ul> <li>3+ years of experience in BI development, including integration of AI/ML tools into analytics workflows.</li> <li>Advanced SQL proficiency and hands-on experience with modern data platforms (e.g., Databricks, Amazon Redshift, Amazon S3, Cloud-based Data Lakes).</li> <li>Proficiency with BI tools like Looker and Power BI, including AI-enhanced features such as PBI Smart visuals and ML integration.</li> <li>Hands-on experience with the modern data stack and orchestration tools (e.g., dbt, Airflow, Prefect), including reverse ETL, data mesh architectures, and real-time personalization.</li> <li>Experience building and optimizing scalable analytics solutions for high-volume data processing in integrated cloud environments.</li> <li>Hands-on experience with machine learning frameworks (e.g., scikit-learn, TensorFlow) and deployment tools (e.g., MLflow).</li> <li>Hands-on experience with generative AI tools and prompt engineering, applied to code generation, data analysis, and automated insight discovery within AI-assisted development workflows.</li> <li>Hands-on experience with cloud-native data and AI services (e.g., AWS Bedrock, Databricks AI/Genie), with the ability to communicate insights effectively to non-technical stakeholders.</li> </ul> <p>Preferred Qualifications </p> <ul> <li>Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related quantitative field.</li> <li>Experience in data-intensive industries (e.g., retail, e-commerce, SaaS, fintech), especially with AI transformation initiatives.</li> <li>Hands-on experience with AI-native BI tools and frameworks supporting conversational analytics and autonomous reporting.</li> <li>Experience with semantic modeling, knowledge graphs, and AI-powered data catalog systems.</li> <li>Proficiency in one or more programming languages (e.g., Python, R, Scala) for advanced analytics, including statistical modeling, experimentation frameworks, and causal inference techniques.</li> <li>Experience building data or analytics products from the ground up (0→1) is a strong plus.</li> <li>Knowledge of emerging technologies such as vector databases, retrieval-augmented generation (RAG), and multi-