• Lead the design and delivery of scalable, end‑to‑end data architectures • Define data standards, governance, and enterprise models • Translate business needs into robust, cloud-based solutions • Architect and implement data solutions (batch and real-time) • Collaborate with global stakeholders • Drive the adoption of modern data platforms (Azure, Snowflake, DBT, Power BI) • Act as main point of contact for cloud partners and internal stakeholders • Develop PoCs to validate emerging technologies • Stay current with data trends and continuous learning

• Design, build and maintain robust data pipelines (ETL/ELT) for structured and unstructured data • Develop and operate data solutions in the Microsoft Azure environment, using Databricks and/or Microsoft Fabric • Use Python and SQL (and frameworks such as PySpark) for data processing, transformation and automation • Contribute to data integration, data modeling, data quality and data provisioning across projects • Work with modern data architecture concepts such as Lakehouse and Medallion architectures • Collaborate with colleagues and clients to translate requirements into clean, maintainable technical solutions

• Support and enhancement of processes in a GCP environment; • Development in Python; • Data ingestion with automated pipelines; • Processing and analysis of large volumes of data; • Simplification aimed at efficiency driven by customer needs; • Data- and fact-driven decision making with ownership; • Continuous, shared learning; • Create/maintain data flows and datasets; • Develop/model databases for dashboards and reports; • Document developed processes; • Gather and clarify database/variable requirements with the business.

• Collaborate with other Engineers and Architects to define the enterprise data architecture roadmap. • Drive the design and optimization of OLTP and OLAP models for scalability, performance, and maintainability. • Establish standards for data modeling, storage, and integration across systems. • Partner with other key stakeholders within engineering in developing a comprehensive data and BI strategy aligned with business objectives. • Define data governance practices, data access control, compliance, and quality standards. • Lead proof-of-concepts (POCs) for new data technologies and frameworks. • Own the architectural review process and guidance to development teams on data-related projects. • Establish and ensure best patterns and practices for ORM usage (Entity Framework and others) and SQL optimization, according to business needs. • Evaluate and recommend where AI/ML can enhance data-driven decision-making. • Stay current with modern data engineering trends, cloud-native architectures, and big data platforms. • Actively participate and take ownership of Data Architecture artifacts via ADR process. • Drive AI adoption by introducing and guiding teams in leveraging AI capabilities within the data engineering space to enhance internal efficiency, innovation, and decision-making in everyday workflows. • Liaison between technology and product teams assisting teams in translating business requirements into tangible architectures that meet business needs now in and in the future. • Design data architectures that accurately reflect and support evolving complex product and business processes and are required by our customer base. • Lead data architecture initiatives, collaborating with cross functional teams, from concept through implementation, including governance and quality frameworks. • Identify opportunities for predictive analytics and advanced modeling. • Support and promote the company values through positive interactions with both internal and external stakeholders on a regular basis. • Other strategic business initiatives or special cross-functional project involvement as required.