Senior Director of Data Engineering & Machine Learning

Role Overview

Join Modus Create as Senior Director of Data Engineering & Machine Learning. You will lead and scale the company’s global Data & ML practice, guiding distributed teams to architect modern data platforms and deliver intelligent AI/ML-powered products. You will connect deep technical expertise with business strategy, mentor leaders, and help drive client growth through pre-sales and solution design.

Key Missions

• Lead and scale the global Data & ML practice across distributed teams
• Define and drive data and machine learning strategy
• Mentor leaders and grow high-performing distributed teams
• Support pre-sales: solution design, proposal development, and expanding Data/ML engagements
• Collaborate cross-functionally (Growth, Partnerships, Operations, Engineering) to deliver client outcomes
• Position Modus as a trusted advisor for data, AI, and machine learning transformation

Responsibilities / What You’ll Do

• Architect and deliver modern, scalable data platforms and AI/ML products
• Translate complex technical capabilities into measurable business impact
• Lead DataOps/MLOps practices for pipelines and ML models, including CI/CD
• Engage with partnerships and capabilities to grow and strengthen delivery
• Advance modernization efforts, including AI, security, and DevSecOps positioning for enterprise clients

Requirements

• 15+ years in data or software engineering; 7+ years leading Data Engineering or ML teams
• Deep expertise with modern data ecosystems: Databricks, Snowflake, Redshift, BigQuery, Spark, Kafka, Airflow, dbt, Kubernetes
• Experience defining machine learning strategy using SageMaker, Azure ML, or TensorFlow
• Hands-on cloud-native platform experience on AWS, Azure, or GCP
• Strong understanding of DataOps, MLOps, and CI/CD for data pipelines and ML models
• Proven pre-sales experience: solution design, proposals, and growing engagements
• Strong stakeholder management across technical and executive audiences
• Demonstrated ability to hire, mentor, and grow distributed teams
• Experience integrating partnerships and acquisition-related capabilities
• Background in regulated or complex industries (e.g., healthcare, finance, life sciences)
• Track record building modular engineering frameworks and scalable best practices

Nice-to-Haves

• Experience positioning AI + Security + DevSecOps modernization within enterprise clients
• Demonstrated success creating inclusive, experimentation-driven engineering cultures

Remote Policy

• 100% remote (role location listed: Madrid, ES).