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Build and maintain ingestion and enrichment pipelines for Preply's lakehouse, ensuring data quality, lineage, observability, and governance. Implement batch and streaming pipelines, data contracts, enrichment logic, versioning, SLOs, and self-service tooling while collaborating with ML, analytics, and product teams.

Build and maintain end-to-end batch and streaming ingestion pipelines, enforce data contracts and quality, implement enrichment and lifecycle management, instrument observability and SLOs, ensure governance and enable self-service ingestion for analytics, ML, and product teams.

Design, build, and maintain reliable batch and streaming ingestion pipelines and data lake components. Implement data contracts, quality checks, enrichment logic, observability, governance, and enable self-service ingestion templates while collaborating with analytics, ML, and product teams.

Identify, recruit, onboard, and manage high-quality affiliates and strategic partners. Scale inbound acquisition and automate onboarding workflows. Create onboarding materials, define commission models, optimize partner performance, report to leadership, and collaborate cross-functionally to maximize ROI and GMV.

Lead technical direction and hands-on delivery across platform squads to improve CI/CD, reliability, scalability, and developer self-service. Drive operability (SLOs, monitoring, runbooks), troubleshoot high-impact production issues, build platform services, mentor senior engineers, participate in on-call, and use metrics to measure outcomes and adoption.

Lead and grow high-performing engineering teams in Growth or Monetization, define strategy, coach engineers, drive delivery and technical decisions, partner with Product/Data/Design, and champion engineering best practices to deliver reliable, high-impact features at scale.

Design, build, and operate scalable batch and streaming ingestion pipelines and a governed data lake. Implement data contracts, validation, enrichment, observability, and governance to ensure reliable, production-grade datasets for analytics, ML, and product teams.

Design, build and own backend features and integrations (primarily using Python/Django), collaborate with cross-functional teams, guide technical decisions, ensure reliability through troubleshooting, monitoring, and scalable architecture, and participate in on-call rotation and continuous improvement.

Design, prototype, and deploy state-of-the-art multimodal neural search and ranking deep learning models for personalized learning; collaborate with product and engineering, mentor junior scientists, and establish ML best practices and production pipelines.

Maintain and improve GTM tech stack and CRM hygiene, build automations, run deal governance, create Salesforce dashboards, analyze funnel and retention metrics, and partner with Sales/Marketing/CS to optimize processes.