Senior BI Engineer

Job Summary

In this role, you will be the senior hands-on engineer helping to establish how SCOR builds, governs and delivers reporting across the organization. You will turn business reporting needs and agreed KPI definitions into reliable, scalable reporting products, semantic models and data requirements. You will work closely with the Head of Reporting & Insights, business and metric owners, Data Foundation teams, Analytics Product teams and platform stakeholders.

You will design and deliver high-quality solutions across Power BI and Palantir Foundry, using governed ADM datasets and certified analytical layers rather than recreating data preparation and business logic in individual reports. You will also help establish common engineering, design and governance standards so that centrally delivered and self-service reporting products are consistent, understandable and trustworthy.

The role will contribute to critical reporting delivery, the rationalization and migration of priority legacy reports, self-service enablement and the development of reusable reporting patterns. This is not only a dashboard development role. It is an opportunity to help build SCOR’s enterprise reporting backbone and prepare trusted reporting assets for future natural-language analytics and AI-assisted insights.

Key duties and responsibilities

Strategic Reporting Delivery: design, build, test and operate high-impact reporting products for SCOR, including ScorCard as the global governed KPI reference, critical operational reports and executive-ready reporting assets.

KPI Implementation & Semantic Models: Translate business-owned Metric Dictionary definitions into reusable semantic models, certified datasets and scalable reporting patterns, ensuring KPIs are calculated consistently and reused across central reports, self-service products and future AI-enabled insights.
Reporting and Data Requirements Translation: Translate business reporting needs into clear KPI, data, dimensionality, granularity and ADM requirements, working with Business, Data Foundation and Analytics Product teams to strengthen Palantir Foundry as the governed reporting basis.
Power BI Engineering: Develop robust Power BI semantic models, datasets, reports and applications following SCOR standards for performance, accessibility, naming, documentation, security, maintainability and user experience.
Palantir Foundry / Analytics Layer Integration: Consume governed ADM datasets and certified analytical layers from Palantir Foundry, ensuring lineage, data quality transparency and metric consistency in collaboration with Data Foundation and Analytics Product teams.
Reporting Migration & Rationalization: Support the assessment, redesign, rationalization and migration of priority reports from legacy tools such as Tableau, SAP BO, Cognos, Excel or local solutions into the target reporting stack, based on business criticality, target tool principles, data readiness and reuse potential rather than report-by-report replication.
Reporting Standards, Governance & Certification: Define and apply reusable report templates, visual design standards, navigation patterns, documentation standards and technical guardrails for official, certified and business-critical reporting, including access controls, validation, release management and certification evidence.
Self-Service Enablement: Create certified datasets, templates, guidance and examples that enable business users to build self-service reporting products within clear governance boundaries, while promoting consistency in data usage, KPI definitions and report design.
Quality, Operations & Technical Leadership: Monitor report usage, refresh reliability, performance and incidents; apply secure access patterns including row-level security where needed; mentor BI engineers and business developers, review technical designs, support delivery partners and continuously improve BI engineering practices at SCOR.
Stakeholder Partnership: Work directly with business analysts, metric owners, data owners and end users to understand reporting needs, challenge duplication, translate requirements into practical solutions and deliver reporting products that are adopted in day-to-day decision-making.

Required experience & competencies

Must-have capabilities

Senior BI Engineering Expertise. You have 6+ years of experience delivering enterprise BI, reporting or analytics solutions in complex organizations. You are comfortable working across the full lifecycle: requirements, data modelling, build, testing, release, monitoring and continuous improvement.
Power BI Expertise. You have deep hands-on experience with Power BI Desktop and Power BI Service, including semantic modelling, DAX, Power Query, workspace management, deployment patterns, report performance optimization, refresh monitoring and security concepts such as row-level security.
Data Modelling & Semantic Layer. You understand dimensional modelling, star schemas, semantic models, KPI definitions, certified datasets and lineage. You know why business logic should be governed and reused rather than duplicated across many local reports.
PySpark SQL & Data Platform Foundations. You have strong PySpark SQL skills and practical experience working with data platforms, data warehouses, lakehouses or analytical data models. You can work with data engineers and data foundation teams to translate reporting needs into practical data requirements.
Governed Reporting & Controls. You understand the difference between exploratory analytics, self-service reporting, official reporting and certified or audited reporting. You can turn governance principles into practical engineering patterns without creating unnecessary bureaucracy.
Reporting Standards & Quality Mindset. You care about report usability, consistency and trust. You can apply standards for design, navigation, naming, documentation, accessibility, performance and maintainability so that reporting products are understandable and reliable.

Product and User-Centric Mindset. You care about adoption, not only delivery. You seek to understand user journeys, decision processes and business workflows, and you iterate quickly to create useful products rather than over-engineered dashboards.
Stakeholder Collaboration. You thrive in cross-functional teams and can work with business experts, data engineers, architects, data owners, metric owners and senior stakeholders. You help translate business needs into technical designs and technical constraints into clear business choices.
Technical Leadership & Coaching. You can guide other engineers, business report builders and external partners, set quality standards, review designs constructively and help build a professional BI engineering capability.
Pragmatic Builder Mindset. You are independent, structured and comfortable working in an evolving environment where not every process is defined yet. You like building standards while delivering useful outcomes.

Strong plus capabilities

Palantir Foundry Experience. Experience with Palantir Foundry, Contour, object-based data models, ontology concepts or comparable governed analytics platforms is a strong plus. Curiosity and ability to learn Palantir Foundry quickly is essential.
Software Engineering Discipline. Experience with version control, documentation, testing, environment separation, peer review, release management and CI/CD tooling such as Git, Azure DevOps or comparable platforms is a strong advantage.
Advanced Data Engineering Exposure. Experience with Python, Spark, Databricks, data pipelines or lakehouse architectures is a plus, especially where it helps bridge reporting requirements with governed analytical data products.
Insurance, Reinsurance or Financial Services Knowledge. Experience in insurance, reinsurance, financial services, finance, controlling, performance management or risk reporting is a plus. Willingness to learn the reinsurance business is essential.
AI-Readiness. Experience connecting BI assets, semantic models or governed data products to natural-language analytics, automated narratives or AI-assisted insight tools is a plus. You understand that trusted metrics and governed data are prerequisites for reliable AI-enabled reporting.

Required Education
Quantitative bachelor's or master's degree (e.g. Data Science, Computer Science, Engineering, Mathematics, Physics, Economics, Finance) or equivalent practical experience.