ADOMIK

• Build and maintain backend services and APIs in Python as part of our MCP project. • Collaborate closely with the Product team to understand requirements, propose solutions, and iterate on feedback. • Optimize existing application code to improve performance and maintainability. • Share best development practices and contribute to technical documentation.

• Ensure data availability and quality for customers by evolving connectors and supporting product changes. • Advance internal ingestion capabilities to maximize customer satisfaction and platform reliability. • Coordinate Support, CSM, Engineering, and QA (and occasionally clients) to secure delivery. • Own relationships with Data Sources (API/reporting providers). • Industrialize connector creation and maintenance (processes, standards, monitoring). • Expand automation and AI usage to reduce manual work and accelerate operations. • Own the roadmap and evolution of connectors and ingestion capabilities to sustain platform reliability and unlock product value. • Deliver data that is available, fresh, and reliable at scale, with clear standards and predictable timelines. • Strengthen operations and incident management with effective, reassuring stakeholder communication. • Increase operational leverage through automation and AI, prioritizing repeatability, throughput, and robustness. • Build constructive relationships with data providers to anticipate changes and minimize disruption. • Align cross-functional teams (Support, CSM, Engineering, QA) on priorities, quality standards, and execution. • Execution principles: Reliability first: data availability and quality at scale. • Leverage and speed: automate repeatable work to increase throughput. • Customer trust: transparent communication and predictable delivery. • Anticipation: proactive management of changes on Data Sources.

Role Description Within the Product team’s “Integration Factory” squad, you lead the roadmap, requirements, and execution for the data connectors that power the Adomik platform. Your goal: ensure data availability and quality at scale while increasing operational leverage through automation, AI agents, and excellent execution. This is a highly technical, hands-on role (building/testing connectors, working with APIs, debugging, automating workflows). We're looking for someone who loves to get their hands dirty with APIs and automation tools. - Ensure data availability and quality for customers by evolving connectors and supporting product changes. - Advance internal ingestion capabilities to maximize customer satisfaction and platform reliability. - Coordinate Support, CSM, Engineering, and QA (and occasionally clients) to secure delivery. - Own relationships with Data Sources (API/reporting providers). - Industrialize connector creation and maintenance (processes, standards, monitoring). - Expand automation and AI usage to reduce manual work and accelerate operations. Qualifications - Comfortable with reporting APIs (reading specs, testing). - Spreadsheet-savvy “Swiss Army Knife.” - Able to start manually and then industrialize via automation. - Experience with automation tools (e.g., Zapier, Make, n8n, Python scripts or similar). - Bonus: LLM prompting, API integrations, workflow orchestration. - Innovation- and impact-oriented PM with an automation-first mindset. - Comfortable experimenting with and integrating AI tools (ChatGPT, Claude, Dust, etc.). - Balanced interest in technical, functional, and analytical topics. - Excellent communicator with customers, partners, and the Engineering Team; strong customer empathy and prioritization skills. - Rigorous, curious, collaborative; strong analytical synthesis. - Fluent in English and French. - You are based in the CET/CEST timezone ± 2h (for team collaboration). - AdTech experience is a plus. Requirements - Reliability first: data availability and quality at scale. - Leverage and speed: automate repeatable work to increase throughput. - Customer trust: transparent communication and predictable delivery. - Anticipation: proactive management of changes on Data Sources. Benefits - Full remote - RTT - Lunch vouchers - Mutuelle & Prévoyance - Regular team-building events

• Deliver end-to-end features, from API design (Ruby on Rails) to user interface implementation (React), ensuring a seamless user experience. • Collaborate closely with the Product team to understand requirements, propose solutions, and iterate on feedback. • Optimize existing application code to improve performance and maintainability. • Take the initiative to improve our architecture, design, and development workflows.

• Ensure data availability and quality for customers by evolving connectors and supporting product changes. • Advance internal ingestion capabilities to maximize customer satisfaction and platform reliability. • Coordinate Support, Customer Success (CSM), Engineering, and QA (and occasionally clients) to secure delivery. • Own relationships with data sources (API/reporting providers). • Industrialize connector creation and maintenance (processes, standards, monitoring). • Expand automation and AI usage to reduce manual work and accelerate operations. • Own the roadmap and evolution of connectors and ingestion capabilities to sustain platform reliability and unlock product value. • Deliver data that is available, fresh, and reliable at scale, with clear standards and predictable timelines. • Strengthen operations and incident management with effective, reassuring stakeholder communication. • Increase operational leverage through automation and AI, prioritizing repeatability, throughput, and robustness. • Build constructive relationships with data providers to anticipate changes and minimize disruption. • Align cross-functional teams (Support, CSM, Engineering, QA) on priorities, quality standards, and execution. • Execution principles: Reliability first — data availability and quality at scale. • Leverage and speed: automate repeatable work to increase throughput. • Customer trust: transparent communication and predictable delivery. • Anticipation: proactive management of changes on data sources.