Role Description In this role, you will help shape the data foundations behind AI-driven products and workflows. As a Senior Data Engineer | Data Ops, you will play a key part in connecting complex data sources, strengthening the reliability of critical systems, and partnering closely with Product, Engineering, and Data Science to support high-impact work across the business. - Lead the Design and Implementation: Architect and maintain high-performance, secure, and scalable data pipelines to support AI-driven workflows. - Drive Integration: Collaborate with cross-functional teams to autonomously manage the ingestion, transformation, and integration of large datasets from external partners. - Enhance Data Quality and Compliance: Build systems to ensure data quality, integrity, and regulatory compliance (e.g., ISO 13485, GDPR). - Build and Automate: Develop reusable code and frameworks to streamline data processes and ensure operational excellence. - Monitor and Troubleshoot: Monitor data pipelines, resolve issues autonomously, and implement safeguards to minimize disruptions. - Innovate: Identify and implement best practices and emerging technologies to enhance data infrastructure and team efficiency. - Collaborate Globally: Serve as a technical expert, working closely with Product, Engineering, and Data Science teams to ensure alignment on project goals and deliverables. Qualifications - 3+ years of experience in DataOps, data engineering, or a similar role, preferably in a regulated industry. - Proficiency with SQL and NoSQL databases and experience designing complex data pipelines. - Expertise in cloud platforms (AWS, GCP, or Azure) and tools like Terraform, Kubernetes, and Docker. - Proven ability to work autonomously, drive projects independently, and deliver measurable results. - Strong communication and leadership skills to mentor team members and coordinate with diverse stakeholders. - Fluency in English and Spanish. Requirements - Familiarity with monitoring tools and data visualization platforms (e.g., Grafana, Power BI). - Exposure to machine learning workflows or AI model integration. Benefits - 🚀 Be part of one of the most disruptive startups in HealthTech and AI and make a difference. - 🏆 Personal and professional growth as part of a fast-growing, international team. - 🎧 No corners cut in having the best tech equipment to do your job. - 🙋 Unlimited remote working environment, where you can choose to work from home and attend our Madrid office whenever you want to. - 📚 Learning and development opportunities and training budget. - 💸 Flexible Remuneration. - 👩🏻‍⚕️ Health Insurance covered by IDOVEN. - 🏋 Access to Wellhub (Gympass), empowering your physical and mental wellness! - 🖥️ Remote Work Allowance for your home office setup! - 🌴 23 holidays, your birthday off, and December 24th and 31st half days to celebrate! - 😎 Regular team events and Thursday happy hours. - And much more! Company Description At Idoven, we believe in hiring top talented people like you - ambitious, forward thinkers who want to make a difference in the world and have an impact. - Diversity & Inclusion: At Idoven, we believe diverse teams build better products. - We are an equal opportunity employer and welcome applicants from all backgrounds, regardless of race, gender identity, age, religion, sexual orientation, or disability.

• Analysierst Kundendaten und entwickelst Machine-Learning-Modelle • Bau und Betrieb von Datenpipelines • Überführung von Modellen in produktionsreife Services • Backend-Entwicklung, wenn erforderlich • Schreiben von wartbarem Code • Übersetzen fachlicher Fragestellungen in konkrete Anwendungsfälle • Aktive Mitarbeit an der Referenzarchitektur

• Design scalable conceptual, logical, and physical data models for ad delivery, audience segmentation, campaign reporting, inventory, and billing. • Map data relationships, dependencies, and flows across existing systems and ensure critical dependencies are preserved in the future-state architecture. • Conduct exploratory data analysis across raw and existing datasets to develop a comprehensive understanding of the current-state data landscape. • Profile existing data sources, inventory and characterize data assets, assess data quality, and identify gaps, inconsistencies, duplication, and integration risks. • Define data ingestion, transformation, and orchestration patterns across batch and real-time data streams. • Design data architectures that support high-volume events such as ad impressions, click activity, audience signals, inventory changes, and campaign transactions. • Architect cloud-native data solutions using AWS services and technologies such as relational databases, graph databases, retrieval-augmented generation, and vector databases. • Define integration patterns between legacy systems and a modern microservices-based platform. • Ensure data interfaces, schemas, contracts, relationships, and system dependencies are clearly defined and documented. • Establish data governance standards across lineage, cataloging, data quality, access controls, privacy, security, and lifecycle management. • Collaborate closely with cloud services, engineering, architecture, product, and business teams across multiple workstreams. • Maintain data architecture artifacts including entity relationship diagrams, data flow diagrams, schema definitions, data dictionaries, and architecture decision records.

• Leverage a dynamic skill set in our rapidly growing Snowflake Environment • Design new software and Data Engineering applications in the Snowflake Environment • Develop advanced Snowflake SQL and ETL code • Implement Snowflake standards and best practices • Work closely with internal stakeholders and business partners • Conduct regular presentations on Data Governance and Snowflake best practices • Author and review Data Governance and Snowflake standards and best practices • Assist Trust and Standards Management in development of standards, guidelines, and best practices • Displays knowledge of and ability to apply project management skills