• Design and implement data solutions using ADF, Microsoft Fabric, Synapse, Databricks • Build data models for scalable data processing, endpoint processing, and integration • Develop and optimize data pipelines (real-time, batch, and BYOD) • Create semantic models and dimensional models in Power BI • Build enterprise dashboards, paginated reports, and self-service analytics solutions • Implement row-level security, complex DAX measures, and model optimizations • Apply DataOps practices, monitoring, and performance tuning • Ensure data security, quality, and governance

Role Description We are looking for motivated individuals to join us on a short-term project (approx. 6 weeks) supporting our Platform Services teams with contract-related tasks in Salesforce, helping ensure data accuracy and consistency across our systems. - Locate, review, and map contracts within Salesforce - Ensure data accuracy and consistency across CRM records - Support data clean-up and quality improvement initiatives - Spot gaps or inconsistencies and flag or suggest improvements - Assist with ad hoc admin and reporting tasks - Collaborate with internal stakeholders when needed Qualifications - Fluent level of English (written and spoken) - Comfortable using computers and working with data (Excel/CRM is a plus) - Strong attention to detail and accuracy - Organised and reliable, able to work independently - Available full-time for ~6 weeks (starting immediately) Company Description Established in 2000, Awin is proud of our dynamic, social and inclusive culture. - Diversity & Inclusion are paramount to us, and we proudly pursue and hire diverse team members. - We champion uniqueness and authenticity; this is who we are at our core. - Our network of affiliate partnerships are diverse and transparent, as are the employees powering our vision to build the world’s leading open partner ecosystem. - We welcome all backgrounds, identities, and experiences. - If you need support at any point in the application or interview process, please let us know.

• Own day-to-day administration, configuration, and health of Oura's global Databricks environment, serving stakeholders across IT, business, and data science domains. • Manage workspace governance: access controls, cluster policies, cost monitoring, job scheduling, and security configurations. • Support onboarding of new teams and use cases onto the Databricks platform as Oura unifies data across Finance, SDM, Commerce, Marketing, and other domains. • Proactively identify and resolve performance bottlenecks, reliability issues, and cost inefficiencies. • Maintain SLAs for platform availability and incident response across global time zones. • Partner with IT and Data Architecture teams to align platform configurations with Databricks best practices and Oura's Data Mesh approach.

• Conduct client data readiness assessments, evaluating source systems, data quality, and migration complexity during early implementation phases. • Define data cleansing, transformation, and validation frameworks to improve migration success rates. • Partner with Implementation Project Managers and Solution Consultants to ensure data architecture supports predictable delivery timelines. • Establish standardized migration playbooks, mapping templates, and reusable ETL frameworks to accelerate onboarding and reduce implementation risk. • Design and maintain conceptual, logical, and physical data models within Microsoft Dynamics 365 (Protech). • Define and document data architecture standards, integration patterns, and governance best practices. • Architect and oversee ETL processes using SSIS and other standard ETL tools. • Design and implement integrations leveraging KingswaySoft and/or Pentaho Data Integration. • Lead data migration strategy and execution support for onboarding and implementation projects. • Identify data dependencies, risks, and integration gaps early in the delivery lifecycle. • Ensure secure, scalable, and high-performance data exchange between D365 and external systems. • Collaborate with Product and Engineering to assess the architectural impact of platform enhancements. • Partner with Analytics teams to ensure reporting accuracy, consistency, and data integrity. • Develop reusable integration templates, migration accelerators, and standardized data patterns. • Proactively identify systemic data design issues and recommend improvements to reduce rework and onboarding delays. • Utilize AI-enabled tools to analyze source system data structures, identify data quality risks, and support scalable migration and integration architectures. • Maintain clear documentation of data flows, mappings, transformations, and integration logic.