Analytics Engineer

• Contributing across the full analytical lifecycle, including data modelling and development and maintenance of Tableau dashboards and reports delivering clear, timely insights to technical and non-technical stakeholders
• Designing, implementing and maintaining high-quality ETL and Lakehouse pipelines across Databricks and Amazon Redshift to support the Single Source of Truth (SSOT) project by centralizing and integrating disparate datasets (e.g. Salesforce/CRM, holdings and finance data)
• Collaborating with Strategy and other business and technology stakeholders to understand key business questions and producing analytical products supporting commercial and strategic objectives
• Developing and enhancing enterprise-grade Tableau dashboards that communicate trends, drivers and performance, meeting standards for performance, usability and interpretability
• Contributing to design decisions around data freshness, transformation layers and analytical layer; proactively identifying data quality issues and partnering with upstream teams to resolve them
• Working closely with the local VP to support team management and strategic planning

Key requirements:

• BS/MS in Computer Science, Data Science, Mathematics, Engineering or related field
• 6+ years in analytics engineering, BI or data engineering, incl. 2-3 years in complex enterprise environments
• Owning end-to-end analytical products (data modeling, transformations, dashboards, stakeholder delivery) at senior IC level
• Building and maintaining ETL pipelines (e.g. Databricks) with proficiency in Python, SQL, PySpark and solid data modelling knowledge
• Owning production reliability, validation, reconciliation against sources, failure resolution and documentation
• Partnering with IT to move analytical solutions through formal SDLC and change-management processes
• Strong collaboration skills, highly organized, working across locations and independently, incl. mentoring juniors

Nice to have:

• Familiarity with financial markets and market data
• Experience with Apache Spark, Amazon S3, Redshift or similar cloud data platforms
• Prior experience in analytics teams within financial services or capital markets
• Familiarity with Salesforce/CRM or similar client data platforms
• Familiarity with Google Cloud / Enterprise AI tools (e.g. Vertex AI, Gemini)
• Exposure to AI-supported analytics or agent design patterns (RAG, orchestration, routing)