• Collaborate with clients to understand business objectives and technical requirements to translate them into effective data solutions • Lead end-to-end delivery of data initiatives: design, build, and optimize scalable data pipelines, data lakes and architectures using Databricks, Fabric, and other modern cloud tools (Snowflake, Azure Data Services, etc.) • Define architectural patterns, reusable accelerators, and modernization frameworks using Databricks, Fabric, Snowflake, Azure, DBT and emerging technologies • Provide architectural governance and oversee multiple engagements to ensure consistency, quality, and alignment with best practices. Proactively managing risks, resourcing, and margin protection • Lead and scale the data engineering practice, including capability building and setting technical standards • Contribute to technical pre-sales, shape solution offerings, and support industry-specific use-case development • Collaborate closely with our partners to align solutions, stay ahead of platform evolution, and build differentiated offerings for our clients • Manage a technical team, providing guidance, mentoring, and support to ensure successful delivery and development of team members • Enable the use and adoption of AI capabilities within existing data platforms and solutions.

• Design, build, and maintain data pipelines for processing large volumes of structured and unstructured data. • Design and implement Data Lakes and Data Warehouses to support analytics and reporting. • Develop and maintain scalable database architectures optimized for performance and reliability. • Integrate data from multiple sources using ETL/ELT processes. • Work closely with analytics and business teams to ensure high-quality data availability. • Optimize data models and storage solutions to improve query performance. • Implement data governance, security, and quality standards. • Support business intelligence platforms such as Power BI for reporting and dashboards. • Collaborate with cross-functional teams in a cloud-based environment.

• You will be a core technical leader and key strategist, responsible for defining, designing, and overseeing the implementation of enterprise data architectures. • You will work at a strategic level with business leaders, data engineering teams, data scientists, and other stakeholders. • Design and define the architectural direction of data systems, including the selection of technologies and platforms. • Lead the design of complex enterprise data models and the data governance strategy. • Define and oversee the implementation of next-generation data platforms for Big Data. • Define and audit data quality and governance policies. • Mentor technical leaders and high-potential talent in data engineering. • Articulate complex technical data strategies to executive and non-technical audiences. • Troubleshoot the most complex problems in distributed data systems. • Develop new models and process frameworks for large-scale data engineering.

• Dedicate ~60% of your time to the programming side: building our data platform, developing ETL processes, managing DAGs, and ensuring our data formation is robust and reliable. • Spend ~30% of your time as a Data Analyst, breaking down business questions from Sales, Marketing, Finance, and Product Managers into actionable data models straight into DAGs. • Work closely with all our relevant internal stakeholders to ensure they have the data they need to drive UpCloud’s growth. • Organize and take ownership of our in-house systems to make data more accessible and useful for every user in the company.