We love technology, and we enjoy what we do. We are constantly driven by curiosity, innovation, and the desire to improve every day. We take ownership of our work, value collaboration, and foster a culture of trust and accountability. Our Enrouters embrace challenges, ask questions, learn quickly, and grow together. We pride ourselves on offering competitive compensation, excellent benefits, a great work environment, flexible schedules, and policies that promote a healthy work-life balance. We care about who you are both inside and outside the workplace, and we are committed to building a strong community of driven, responsible, respectful—and above all—happy individuals. We want you to genuinely enjoy working with us. We are seeking a data-driven Ai Engineer to join our team at a high-growth advertising technology company. This role focuses on scaling our reporting infrastructure for advertising performance and billing reconciliation, ensuring that financial and operational data is accurate, automated, and actionable. In this role, you will be responsible for developing robust data pipelines, ensuring data quality and reliability, and enabling efficient data consumption across the organization. You will collaborate closely with cross-functional teams including Product, Engineering, Analytics, and Business stakeholders to deliver high-impact data platforms. The ideal candidate is a proactive problem-solver with strong technical expertise, capable of working with large datasets, modern data architectures, and cloud-based environments. You thrive in fast-paced settings, navigate ambiguity with confidence, and are passionate about turning data into actionable value.

• Execute business-side data migration activities for Commercial and Procurement data objects (Direct and Indirect), in line with global, regional, and country-specific deployment requirements and timelines. • Plan and deliver data migration activities aligned with the Client’s rollout plan and key milestones. • Coordinate and perform data cleansing to ensure high data quality and compliance with defined standards. • Collect, validate, and complete data for manual or constructed data objects, ensuring accuracy and completeness. • Collaborate with IT and technical teams to define, validate, and maintain mappings between legacy systems and target solutions. • Create and maintain master data lists for Commercial and Procurement objects, as required. • Provide business insights and detailed input to support data extraction and transformation processes. • Ensure data readiness across the migration lifecycle, including quality checks, validation, and issue resolution. • Validate that data supports business processes (including Order to Cash) and meets stakeholder requirements. • Perform manual data loads into target systems where required, following governance and control procedures. • Execute data validation checks and provide results, insights, and approvals. • Support testing phases (SIT, UAT, mock loads), including defect identification, triage, and resolution. • Support cutover activities, including final data loads, reconciliation, and validation. • Work closely with the Client’s global data migration team and ensure alignment with delivery frameworks. • Collaborate with business stakeholders, SMEs, and technical teams across regions. • Identify and document business requirements and local market specifics impacting data migration. • Participate in project meetings, including workstream sessions, defect triage, and cutover planning.

We are seeking a highly skilled Data Engineer with extensive experience in Azure Data Lake to contribute to our dynamic team at Creative Chaos. The ideal candidate will be responsible for architecting, developing, and optimizing data pipelines that will facilitate the efficient processing of large datasets. **Responsibilities:** - Designing and implementing robust data pipeline solutions within Azure Data Lake. - Integrating and transforming data from various sources to enable comprehensive analytics and reporting. - Ensuring data quality and integrity, implementing data governance practices. - Collaborating with cross-functional teams to understand data requirements and develop scalable solutions. - Monitoring and optimizing data processing workflows for performance and reliability. - Documenting processes and architecture to ensure maintainability and scalability. - Staying abreast of new Azure technologies and best practices for data engineering.

• Design and implement robust data pipelines, build scalable data lakes. • Enable business insights through efficient data systems. • Collaborate with analysts and stakeholders to define data requirements and support business intelligence efforts. • Monitor and troubleshoot data pipelines to ensure smooth operation. • Stay updated on industry trends and best practices in data engineering.