Eneba

Operations

• Own end-to-end performance of your division, ensuring metrics like FRT and FCR are met.
• Coach and develop Managers to build a strong leadership unit.
• Monitor daily queues and intervene as necessary.
• Collaborate with Quality, Automation, and WFM teams for operational efficiency.
• Assist in staffing and scheduling decisions.
• Provide insights and reports to Head of Operations.

Operations Manager, CS

Recruitment

• Take full ownership of key hiring initiatives for the selected organizations: product, engineering, marketing, creative, finance, legal, operations, sales, and/or customer support.
• Split role focus: individual contribution towards hiring goals and team (or program) leadership responsibilities.
• Shape the future of Eneba: build creative and resourceful strategies to secure top talent for business critical functions.
• Setup and track success metrics across the entire candidate and interviewer journey.
• Partner with the leadership team, drive cross-functional alignment, and foster team collaboration.

Talent Acquisition Partner

Customer Support

• Own and continuously improve the CX quality framework across customer support interactions, ensuring consistent evaluation standards and actionable feedback loops.
• Analyze customer feedback, support tickets, and operational data to identify recurring issues, root causes, and opportunities to improve the customer experience.
• Monitor and report on key CX metrics such as CSAT, CES, NPS, FCR, and ticket trends, using insights to prioritize improvements and measure impact.
• Build and maintain data dashboards and reporting frameworks to surface CX performance insights and support data-driven decision making.
• Map and evaluate the end-to-end customer journey, identifying friction points and recommending improvements across touchpoints.
• Partner closely with Product, Operations, and Training teams to address systemic issues and translate customer insights into product, process, and policy improvements.
• Drive continuous improvement initiatives within the support organization, focusing on operational efficiency, quality standards, and customer outcomes.
• Translate quality and customer insights into training materials, coaching programs, and process improvements to elevate support team performance.

Customer Experience Analyst

Influencer Marketing

• Lead a dedicated sub-team within the Influencer Marketing function
• Conduct regular 1:1 meetings to coach, support, and challenge team members
• Set clear goals and performance expectations aligned with business targets
• Monitor individual and team KPIs and ensure consistent target achievement
• Drive accountability and actively push for ambitious results
• Identify performance gaps and implement structured improvement plans
• Support career development through feedback, growth plans, and skill-building initiatives
• Foster a high-performance, results-driven team culture
• Own and execute influencer strategy across selected markets or products
• Manage relationships with creators, agencies, and key partner
• Lead testing initiatives and scale successful experiments
• Optimize campaigns based on performance data and ROI
• Collaborate closely with cross-functional stakeholders
• Introduce structure to processes, reporting, and performance management
• Contribute to long-term team scalability and organizational design

Influencer Manager

• Take full ownership of Eneba’s talent acquisition delivery and make sure hiring supports the business effectively, consistently, and at pace.
• Build and run a data-driven, AI-enabled Talent Acquisition function that continuously improves how we hire.
• Turn hiring goals into clear execution plans and ensure they are delivered with high quality.
• Raise the hiring bar across the company by setting strong standards for assessment and decision-making.
• Use data and insights to identify opportunities to improve speed, quality, and efficiency in recruitment.
• Continuously review and refine recruitment processes to keep them simple, scalable, and effective.
• Identify bottlenecks early and address them before they slow the business down.
• Partner closely with hiring managers to create clarity, alignment, and fast decision-making.
• Lead, develop, and performance-manage a Talent Acquisition team, creating a culture of ownership and accountability.
• Introduce and optimise modern recruitment tools, automation, and AI to reduce manual work and increase impact.

Head of Talent Acquisition

Performance Marketing

• Lead, develop and scale a high-performing Google Ads team across multiple global markets
• Own overall performance across Search, Shopping and Performance Max with full revenue responsibility
• Manage large multi-country accounts with significant daily budgets
• Set clear performance targets aligned with business and margin goals
• Structure account strategy across markets, categories and product priorities
• Review campaign structures, feed logic and performance strategy to ensure high standards
• Support launches of new products and new geographies from a paid acquisition perspective
• Work closely with Commercial, Product and Marketing teams to align paid strategy with business growth
• Develop team processes, testing frameworks and scaling strategies
• Drive adoption of AI, automation and new Google features within the team
• Stay hands-on enough to challenge strategy, guide optimization and step in when needed

Google Ads Team Lead

Machine Learning Engineer

• Build and iterate on real-time fraud/risk models (e.g., gradient boosting and anomaly detection approaches) to score transactions during checkout and support Risk decisioning.
• Own the full ML lifecycle for fraud detection models: data exploration, feature engineering, training, evaluation, deployment, monitoring, and continuous improvement.
• Design robust evaluation strategies for rare-event, highly imbalanced data, including handling delayed/partial ground truth and defining metrics aligned with business constraints.
• Partner closely with Risk, backend, and Data/Platform teams to productionize models behind an API, integrate with the risk engine, and improve model-driven decision flows (pre-/post-authorization).
• Drive experimentation and feedback-loop initiatives to improve labels and model quality over time, while maintaining strong reliability, observability, and documentation.