Senior Data Strategy Analyst

Description

Job Summary: We are looking for a Senior Analytics Engineer to build the analytical and semantic layer, transforming raw data into reliable, production-ready models. Key Highlights: 1. Building the analytical and semantic data layer 2. Transforming raw data into reliable and performant models 3. Acting as a bridge between business and engineering, translating requirements Senior Data Strategy Analyst Full\-time Employee Status: Regular Role Type: Home Department: Data Management Schedule: Full Time **Company Description** ----------------------- Serasa Experian is Brazil’s first and largest Datatech company. A leader in risk and opportunity intelligence solutions, focused on credit, authentication, and fraud prevention journeys. With cutting-edge technology, innovation, and top talent, we transform risk uncertainty into the best decision—helping individuals achieve their dreams and enabling businesses of all sizes and sectors to thrive. We have 22\.000 people operating across 32 countries, and every day we invest in new technologies, talented professionals, and innovation to help all our clients maximize every opportunity. Headquartered in Dublin, Ireland, Experian is listed on the London Stock Exchange (EXPN) and is a constituent of the FTSE 100\. **Job Description** ------------------- We are seeking a **Senior Analytics Engineer** to strengthen our data team. This person will be a key contributor to building the **analytical and semantic layer**, transforming raw data into **reliable, performant, and consumption-ready models**, enabling actionable insights, consistent metrics, and scalable data products. We work with **Databricks/Lakehouse**, and we seek someone who enjoys combining **engineering \+ data modeling \+ business rules**, with attention to governance, quality, and the analytical user experience (BI/consumption). In a modern context, this directly connects to governance and discoverability via catalog (e.g., Unity Catalog) and “translating” data into business concepts. Responsibilities * **Design and evolve analytical data models** (facts, dimensions, aggregations, metrics/KPIs), focusing on **Gold and Semantic layers**, ensuring consistency and reusability. * Implement **data modeling standards** (e.g., medallion architecture) and best practices for delivering data for analytical consumption, with attention to **contracts, granularity, compliance, and traceability**. * Act as a bridge between **business and engineering**, translating requirements into well-defined **models and datasets** (metric definitions, rules, hierarchies, conformed dimensions). * Ensure **data quality and reliability** (testing, validation, controls, cross-layer consistency), reducing rework and increasing trust. * **Optimize model and query performance** (Databricks SQL/Delta), including physical design and choices that improve cost/latency for consumption. * Collaborate on evolving the analytical architecture and data ecosystem (governance, catalog, observability, development standards). * Support stakeholders and analytics/BI teams in correct data usage (documentation, data discovery, enablement, continuous improvement). Requirements * Solid hands-on experience with **SQL** and **Python** applied to analytical pipelines and modeling. * Practical development experience with **Databricks** (notebooks, jobs/workflows, and/or Databricks SQL). * Experience with **data modeling for analytics**, especially in **Gold** and **semantic layer** contexts (metrics, dimensions, fact tables, conformance). * Familiarity with **cloud environments** (AWS, Azure, or GCP). * Engineering best practices: **version control (Git)**, documentation, and collaboration (e.g., Confluence, PR standards). * Clear communication and ability to **explain concepts and metrics** to both technical and non-technical audiences. Differentials * **Power BI**: experience with **dimensional modeling**, **semantic layer**, and especially **performance** (e.g., model design, cardinality, relationships, best practices for queries and consumption). * Experience with **dbt, Airflow**, or orchestration/transformation tools (beyond native Databricks capabilities). * Experience with **observability/data quality** (testing, expectations, alerts, SLAs). * Domain experience in **collections, finance, or operations**. * Experience with advanced analytics initiatives (predictive/ML) and their dependency on reliable, governed data. **Qualifications** ------------------ * sql * databricks * semantic layer * data modeling **Additional Information** -------------------------- Serasa Experian is much more than you imagine. With the purpose of creating a better future by expanding opportunities for people and businesses, in Brazil we are over 4,000 people working across diverse teams and specialties. Here, each skill and diversity complements the other—you can work on what you love most. We are committed to building an inclusive culture and an environment where people can balance their careers with personal commitments and interests, prioritizing well-being. We dedicate ourselves to being one of the best and most innovative companies to work for in the country, enabling incredible experiences and careers for our people. Our strong “people-first” approach is externally recognized through numerous market certifications: we’ve been awarded by Great Place To Work™ in 24 countries and received the international Top Employers certification, besides being recognized as one of the best companies for young professionals and holding a 4.6 rating on Glassdoor. Each recognition confirms we’re on the right path—providing an ever-better workplace for our talents. Experian Careers \- Creating a better tomorrow together **Job Location** ---------------- I'm interested Privacy Notice Cookies Settings