Data Analyst

Location:
Brussels, Belgium Company: Tata Consultancy Services (TCS) Belgium Employment Type: Full-time Nature of the Tasks Collect and clean data from various sources. Analyse datasets to identify trends and patterns. Create interactive dashboards and reports that utilize data storytelling to effectively present findings, with defined refresh cadences and Service Level Agreements (SLAs) for key deliverables. Collaborate with stakeholders to understand data needs. Develop and maintain data dashboards and reporting tools that provide intuitive access to key metrics and insights, supported by clear documentation and update schedules. Perform statistical analysis to support decision making. Ensure data accuracy and consistency through the implementation of data quality checks, validation rules, and regular reconciliation processes with source systems. Conduct exploratory data analysis to uncover insights. Document methodologies and analysis processes. Recommend improvements based on data insights. Partner with Data Engineers on data modelling (e.g., star/snowflake schemas) and contribute to a centralized definitions and metrics catalogue. Present data-driven insights and create actionable, decision-oriented recommendations tailored for non-technical audiences and stakeholders. Write complex Structured Query Language (SQL) queries for data extraction and transformation, and optimize them for performance and efficiency. Specific Expertise and Technologies Knowledge of data analysis and manipulation using SQL, Python, or R to extract, transform, and analyse structured and unstructured datasets. Experience with data visualization and reporting tools (e.g., Power BI, Qlik, Microsoft Fabric) to design interactive dashboards and reports. Knowledge of statistical analysis methods and tools (e.g., SPSS, R, Python libraries) to support evidence-based insights. Familiarity with spreadsheet tools, especially Microsoft Excel. Knowledge of data warehousing concepts and platforms (e.g., star/snowflake schemas, Microsoft Fabric, Snowflake, BigQuery) to support scalable reporting. Knowledge of data preparation and transformation tools (e.g., Alteryx, Power Query, dbt) to ensure clean and reliable datasets. Ability to work with large datasets and databases. Awareness of basic machine learning algorithms (e.g., regression, clustering, classification) to support advanced analytics in collaboration with data scientists. Knowledge of ETL processes and orchestration tools (e.g., SSIS, Informatica, Talend, Azure Data Factory) to support data pipelines. Knowledge of cloud-based data services (e.g., Microsoft Fabric, Azure Synapse) to enable scalable and modern analytics. Knowledge of data quality practices (e.g., validation rules, reconciliation, lineage tracking) to ensure accuracy and consistency of insights. Knowledge of metadata and cataloguing tools (e.g., Azure Purview, Collibra) to support data governance and discoverability. Minimum Level of Expertise Junior for analysts supporting a senior team. Normal for standalone Data Analysts accountable for business domains. Certification and/or Standards Optional for 'Junior' level: A certification directly related to the requested profile. Optional for 'Normal' level and above: Microsoft Power BI Data Analyst Associate Microsoft Azure Data Engineer Associate Fabric Analytics Engineer Associate Fabric Data Engineer Associate Or an equivalent certification Skills Ability to analyse datasets, detect trends, and deliver evidence-based insights. Skill in presenting findings with visuals and storytelling that support decisions. Commitment to maintaining accuracy, consistency, and integrity in reporting. Ability to resolve data issues and propose actionable improvements. Competence in managing tasks and delivering insights on time. Drive to explore new methods, tools, and data sources proactively. Ability to interpret analytical findings to tell a compelling story that clearly prescribes business actions and drives strategic decision-making. Flexibility to adopt new data platforms, tools, and approaches. Ability to frame insights into narratives that support decisions. Ability to participate in multilingual meetings. Ability to understand, speak, and write English, optionally French as an additional asset. Excellent interpersonal skills. Ability to work in a team as well as autonomously. Results-oriented mindset, focused on delivering. Ability to present insights concisely for senior decision-makers.