• 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.

• Leads the development and implementation of comprehensive, enterprise-wide data architecture frameworks that ensure consistency, scalability, and alignment with the organization’s strategic goals. • Oversees data architecture initiatives across multiple business units, ensuring seamless design and delivery of complex data solutions that address enterprise needs. • Conducts architecture reviews and ensures that solutions meet scalability, security, performance, and reusability standards across the organization. • Develops and maintains a forward-looking data architecture vision and roadmaps that supports the organization’s long-term business strategy and digital transformation goals. • Oversees enterprise-scale data integration initiatives, ensuring that data from multiple, diverse sources is integrated into a cohesive and unified architecture that supports business intelligence and advanced analytics. • Provides technical leadership for data architecture, ensuring that advanced data modeling, storage, and integration practices adhere to industry best practices and organizational standards. • Incorporates data governance principles into architectural decisions, ensuring that data management practices adhere to organizational policies. • Establishes and oversees data quality standards, including data cleaning, validation, and monitoring processes. • Ensures that data security measures, such as access control and encryption, are appropriately implemented for sensitive data. • Serves as the primary liaison to executive leadership on data architecture strategy, presenting strategic recommendations and influencing key decisions for enterprise data initiatives. • Translates complex technical and architectural concepts into clear, business-relevant insights, ensuring alignment between data strategies and overall business outcomes. • Builds and nurtures relationships with executive leadership, IT, and business unit leaders to champion the data architecture strategy across the organization. • Shapes the future direction of the organization’s data architecture by staying informed on emerging technologies, evaluating their potential adoption, and leading the execution of future-state architectures. • Develop in-depth knowledge of AI/Gen-AI impacts on Data engineering & management capabilities and work with AI/Innovation team to bring most relevant AI led intervention for Data teams. • Evaluates new tools, platforms, and systems that could enhance the company’s data infrastructure Collaborates with executive leadership to drive innovation and ensure the organization remains competitive by leveraging cutting-edge technologies and data practices. • Champions proof-of-concept initiatives for new technologies and data solutions that align with the organization’s strategic vision. • Provides mentorship and leadership to data architects, engineers, and cross-functional teams, fostering talent and ensuring high-quality architecture solutions. • Leads and guides cross-functional teams in the design and delivery of data architecture solutions, ensuring timely execution and adherence to enterprise standards.