Company description Re:Sources is the backbone of Publicis Groupe, the world’s third-largest communications group. Formed in 1998 as a small team to service a few Publicis Groupe firms, Re:Sources has grown to 4,000+ people servicing a global network of prestigious advertising, public relations, media, healthcare and digital marketing agencies. We provide technology solutions and business services including finance, accounting, legal, benefits, procurement, tax, real estate, treasury and risk management to help Publicis Groupe agencies do what they do best: create and innovate for their clients. In addition to providing essential, everyday services to our agencies, Re:Sources develops and implements platforms, applications and tools to enhance productivity, encourage collaboration and enable professional and personal development. We continually transform to keep pace with our ever-changing communications industry and thrive on a spirit of innovation felt around the globe. With our support, Publicis Groupe agencies continue to create and deliver award-winning campaigns for their clients. Overview Publicis Groupe is building a modern, scalable ETL and analytics platform that enables end users to ingest, access, analyze, and report on data across the organization. We are seeking a Data Analyst to help transform complex data into actionable insights, support business decision-making, and ensure data quality and usability across the platform. This role works closely with data engineering, AI, UX, and full-stack development teams to validate data pipelines, define metrics, and deliver meaningful reports and dashboards to internal stakeholders. Responsibilities Data Analysis & Insights Generation Analyze and interpret data produced by enterprise ETL pipelines. Identify trends, anomalies, and actionable insights to support operational and strategic decision-making. Translate business questions into data queries and analytical outputs. Data Quality & Validation Validate data quality, accuracy, and completeness across ingestion and transformation processes. Ensure consistency of metrics and reporting across the platform. Reporting & Data Visualization Develop dashboards, reports, and self-service analytics solutions for end users. Define and standardize reporting logic to ensure clarity and usability of insights. Stakeholder Engagement & Business Translation Partner with business stakeholders to define reporting requirements, KPIs, and success metrics. Act as a bridge between business needs and technical data solutions. Data Engineering Collaboration Collaborate with data engineers to troubleshoot data issues and optimize data pipelines. Support the continuous improvement of data infrastructure and workflows. AI & Advanced Analytics Support Support AI and advanced analytics initiatives by preparing, validating, and structuring datasets for modeling and analysis. Documentation & Data Governance Document data definitions, metrics, and reporting logic to ensure transparency and standardization. Advocate for data governance, data literacy, and best practices across the organization. Agile & Cross-Functional Collaboration Participate in Agile ceremonies and collaborate with cross-functional teams to deliver data-driven solutions. Qualifications Qualifications Bachelor’s degree in Data Analytics, Computer Science, Statistics, Mathematics, or related field preferred Fluent in English 3–5 years of experience working as a Data Analyst or in a similar role Strong SQL skills and experience querying large datasets Experience working with data warehouses and analytical datasets Proficiency with BI and visualization tools (e.g., Tableau, Power BI, Looker, or similar) Experience validating and analyzing data produced by ETL pipelines Strong analytical and problem-solving skills Ability to communicate data insights clearly to technical and non-technical audiences Experience working in Agile or product-based teams Preferred Qualifications Experience supporting enterprise data platforms or analytics products Familiarity with Databricks, data lakes, or cloud-based analytics platforms Exposure to Python or similar languages for data analysis Experience working alongside AI or machine learning teams Knowledge of data governance, metadata management, or data catalogs