Senior Data Analyst | Python + PySpark

Description

Job Summary: At Avanade, you will design, build, and evolve data platforms that enable analytics, AI, and digital products at scale, driving innovation and digital transformation. Key Highlights: 1. Transform data into decisions that drive customers 2. Real impact, continuous learning, and collaboration 3. Your ideas become deliverables that make a difference Job Description At Avanade, you will transform data into decisions that drive our customers. This role is critical to designing, building, and evolving data platforms that enable analytics, AI, and digital products at scale. Your work will accelerate innovation and digital transformation by connecting data from multiple sources to secure, reliable, and value-driven solutions. If you seek real impact, continuous learning, and collaboration with diverse and talented people, this is the place for you. Here, your ideas become deliverables that make a difference for enterprises and society. **Together we do what matters.** **Learn more about some of our benefits:** * Meal or food allowance * Multibenefit Card (up to Senior Consultant) * Health and dental insurance * Certifications and training * Life insurance * Private pension * Avababy: Pregnancy support and welcome kit for new parents * Company profit-sharing program * Wellhub * Childcare assistance * Career mentoring * Birthday Off policy (for you and children up to 12 years old) * Well-being sessions * For managerial roles: Corporate vehicle, parking, and fuel allowance **Responsibilities** * Design, build, and maintain data pipelines (batch and/or streaming) using **Python/PySpark** and **SQL**. * Develop and orchestrate robust, observable **ETLs/ELTs**, with logging, metrics, and alerts. * Model data across **transactional (OLTP)** and **analytical/multidimensional (OLAP)** layers for consumption by BI, Analytics, and AI. * Ensure code and artifact quality, versioning, and reproducibility using **GitHub** (branches, PRs, code review). * Implement tests (unit, integration, and data tests) and **plan end-to-end testing strategies**. * Apply best practices in **software architecture** (modularity, security, performance, cost). * Collaborate with analysts, data scientists, and product teams to translate business requirements into scalable solutions. * Document data, processes, and architectural decisions to foster shared knowledge. * Support continuous improvement: automation, standardization, and performance optimization of data environments. Qualifications **Skills and Experience** * Proficiency in **Python** and **PySpark** for data manipulation, transformation, and distributed processing. * Strong knowledge of **SQL** (modeling, tuning, CTEs, window functions, partitions). * **Transactional (OLTP) and multidimensional (OLAP) data modeling**. * **Experience developing ETL/ELT** and orchestration (e.g., Airflow, Databricks Jobs, or similar). * **Knowledge of software architecture** applied to data (design patterns, security, scalability, cost). * Hands-on experience with **GitHub** (GitFlow, PRs, semantic versioning, basic Actions). * **Test development and planning**, including data tests (e.g., data quality, schema validation). **Desirable:** * **CI/CD pipelines for data** (e.g., GitHub Actions, Azure DevOps, automated testing, job/notebook deployment). * **Unstructured databases** (e.g., Data Lake, NoSQL, document, columnar, graph). * Experience with cloud platforms (preferably **Azure**: Data Lake Storage, Databricks, Synapse, Fabric, Key Vault). * Exposure to data governance/security (data lineage, catalog, RBAC/ABAC). **Differentiators:** * Microsoft Azure: *DP\-203 (Data Engineering on Microsoft Azure)*, *AZ\-900*, *DP\-900*, or related certifications. * Databricks: *Lakehouse Fundamentals* or *Data Engineer Associate/Professional*. * English: **Intermediate to advanced**