Senior Data Analyst/ BI Consultant

Senior Data Analyst / BI Consultant Data Platform Transformation NTT DATA Luxembourg NTT DATA Luxembourg brings together 400+ consultants supporting a diverse portfolio of clients across complex technology and transformation environments. Our teams combine strong local proximity with the international capabilities of the NTT DATA Group, with expertise across consulting, cloud, data and AI, cybersecurity, applications, infrastructure and digital transformation. For one of our clients in the insurance sector, we are currently looking for a Senior Data Analyst / BI Consultant to support operational data activities and contribute to the transformation of a modern data platform. THE OPPORTUNITY This opportunity sits at the intersection of data analysis, business intelligence, insurance operations and technology transformation. You will work closely with operational teams responsible for claims, policy lifecycle management and premium administration. You will help these teams investigate complex data topics, improve reporting, define reliable performance indicators and turn operational information into actionable business insights. The assignment is also part of a broader transformation towards a new data platform based on an updated functional architecture and modern data technologies. You will contribute to this transition by improving analytical datasets, data transformation processes, reporting solutions and governance practices. The role requires a consultant who is comfortable working directly with business stakeholders while maintaining a strong hands-on involvement in SQL, data analysis, BI and data transformation. YOUR ROLE As a Senior Data Analyst / BI Consultant, you will take ownership of analytical topics from the initial business question through to the delivery of reliable insights, dashboards or data products. You will analyse information across several operational and analytical systems, identify inconsistencies and investigate their root causes. You will work with business teams to understand operational processes and ensure that analytical outputs accurately reflect the underlying activities. You will also contribute to the design and improvement of domain-level datasets, reporting solutions and data transformation pipelines. In collaboration with Data Science and AI teams, you may help prepare and industrialise predictive use cases. Beyond hands-on delivery, you will communicate findings to stakeholders, challenge assumptions constructively and help less experienced analysts strengthen their analytical practices. WHAT YOU WILL DO
• Analyse the data and reporting needs of operational teams responsible for claims, policy lifecycle management and premium administration.
• Translate business questions into clear analytical requirements, relevant data models, dashboards, KPIs and actionable insights.
• Lead complex analytical investigations involving information from several operational and analytical systems.
• Perform cross-system data reconciliations, identify inconsistencies and investigate the underlying causes of data-quality or reporting issues.
• Write, review and optimise SQL queries using data warehouse and dimensional modelling principles.
• Design advanced dashboards, reports and visualisations using Power BI, SAS Visual Analytics, Apache Superset or comparable technologies.
• Define robust KPIs and help ensure that definitions, calculation rules and interpretations remain consistent across business departments.
• Apply statistical and numerical analysis techniques to identify trends, anomalies, operational risks and opportunities for value creation.
• Manage and improve domain-level datasets in accordance with data governance and Data Mesh principles.
• Contribute to the development and optimisation of ETL and data transformation pipelines using SAS Enterprise Guide, dbt or similar tools.
• Support the transition towards a new data platform and contribute to the adoption of its functional architecture, tools and working practices.
• Collaborate with Data Science and AI teams to prepare, validate and industrialise relevant predictive use cases.
• Present analytical findings clearly to business and technical stakeholders, adapting the level of detail to the audience.
• Challenge ideas and assumptions constructively while maintaining effective working relationships with stakeholders.
• Support junior analysts through guidance, reviews, knowledge sharing and the promotion of good analytical practices. WHAT WE ARE LOOKING FOR Mandatory requirements
• Between 3 and 8 years of professional experience in data analysis, business intelligence or a closely related field.
• Strong practical knowledge of SQL, including the ability to investigate complex data issues and work with large or interconnected datasets.
• Good understanding of data warehouse concepts, including dimensional modelling, star schemas and normalisation.
• Hands-on experience with ETL or data transformation tools such as SAS Enterprise Guide, dbt or comparable technologies.
• Practical experience with at least one relevant BI or data visualisation platform, such as Power BI, SAS Visual Analytics or Apache Superset.
• Experience designing dashboards, reports and data visualisations for operational or business stakeholders.
• Proven ability to define KPIs, document calculation rules and ensure consistent interpretation across different teams.
• Ability to interpret complex datasets and apply appropriate statistical or numerical analysis techniques.
• Familiarity with data governance principles and Data Mesh concepts.
• Experience translating business needs into analytical solutions and measurable operational insights.
• Strong communication and stakeholder-management skills.
• Ability to explain complex analytical findings clearly to both technical and non-technical audiences.
• Ability to influence stakeholders and challenge ideas constructively and respectfully.
• Autonomy, accountability and a strong sense of ownership.
• Ability to manage analytical activities from initial investigation through to delivery and communication.
• Professional fluency in French. Nice to have / Particularly valuable
• Working knowledge of English.
• Previous professional experience in the insurance sector.
• Knowledge of insurance processes related to claims, policy lifecycle management or premium administration.
• Experience supporting a data platform modernisation or transformation programme.
• Experience working with Data Science or AI teams on predictive analytics use cases.
• Exposure to the industrialisation of analytical models or predictive solutions.
• Experience mentoring junior analysts or contributing to an internal data community.
• Interest in innovation, continuous learning and the improvement of data and operational processes. THE ENVIRONMENT Technologies and concepts: SQL, data warehousing, dimensional modelling, star schemas, normalisation, ETL, data transformation, SAS Enterprise Guide, dbt, Power BI, SAS Visual Analytics, Apache Superset, Data Mesh, data governance, KPI management, statistical analysis and predictive analytics. Business domains: insurance operations, claims, policy lifecycle management, premium administration, operational reporting, cross-system reconciliation and business performance analysis. WHY THIS ROLE
• Work directly with operational teams on data topics that influence claims, policy and premium-management activities.
• Take ownership of complex analytical investigations involving several systems, stakeholders and business processes.
• Contribute to a significant data platform transformation supported by modern data architecture and tooling.
• Combine hands-on SQL and BI delivery with data governance, stakeholder engagement and operational improvement.
• Help establish reliable KPI definitions and improve confidence in operational reporting.
• Collaborate with Data Science and AI specialists on the preparation and industrialisation of predictive use cases.
• Share your experience with other analysts and contribute to the development of stronger analytical practices. Desired Skills and Experience SQL Data Analysis Business Intelligence Power BI Data Warehousing Dimensional Modeling ETL dbt SAS Data Visualization