Data Leader

We are seeking a Senior Data Engineering Manager to drive our data strategy, building scalable platforms and teams that power next-generation solutions.

In this pivotal leadership role, you will bring technical vision and expertise, guiding the development and deployment of cutting-edge data products aligned with our business goals.

You will lead multidisciplinary teams – including data engineers, machine learning engineers, and platform architects – fostering a culture of technical excellence and collaboration.

Working closely with stakeholders, you will translate needs into innovative solutions that deliver measurable business value.

As a key member of our engineering team, you will play a central role in bringing our data product vision to life.

• Strategy Development: Define and execute the overall data strategy, directly supporting our industrial product vision and roadmap.
  
• Platform Architecture: Architect and oversee end-to-end development of our data platforms, ensuring scalability, security, and modularity.
  
• Team Leadership: Lead, mentor, and retain high-performing teams, promoting a culture of innovation and ownership.
  
• Data Governance: Implement and enforce best practices for data governance, quality, privacy, compliance, and responsible AI aligned with industry regulations.
  
• Budget Management: Manage budget and resource planning, hiring, and professional development for the data organization.
  
• Strategic Partnerships: Cultivate strategic partnerships, evaluate third-party technologies, and lead platform evolution.
  
• Data-Driven Mindset: Champion a data-driven mindset, empowering all functions to leverage AI for informed decision-making.
  
• KPI Tracking: Establish and track KPIs to measure the business impact of data solutions.
  

• Educational Background: Bachelor's or higher degree in Computer Science, Engineering, Mathematics, Statistics, or a related STEM field.
  
• Technical Experience: Solid experience in technical leadership of end-to-end data, AI, and ML projects, including managing multidisciplinary engineering teams.
  
• Technical Skills: Proven hands-on expertise in Python, software engineering, cloud platforms (AWS, Azure, GCP), data architecture, and scalable data pipelines.
  
• AI/ML Expertise: Deep familiarity with AI/ML frameworks and tools (Scikit-Learn, TensorFlow, PyTorch, HuggingFace, etc.), MLOps best practices, and platform development.
  
• Robust Platforms: Track record in building robust internal platforms, APIs, and data/ML products with a focus on quality, security, and reliability.
  
• Governance and Compliance: Experience implementing governance, privacy, and compliance standards, with a strong commitment to ethical and explainable AI.
  
• Strategic Planning: Strategic planning, project portfolio management, and the ability to influence both technical and non-technical audiences.
  
• Communication Skills: Excellent communication and stakeholder management skills.
  
• Language Proficiency: Fluent English.
  

• Profit Sharing: Possibility of extra compensation based on company performance, according to your performance.
  
• Health and Dental Plan: To ensure your care and well-being.
  
• Flexible Benefit: Receive an amount that can be used according to your needs, including food, transportation, education, culture, and health.
  
• Flexible Hours: Work at the best time for you and have a better quality of life.
  
• Wellness Programs: Massages and manicures in the office, so you can relax and feel good about yourself.
  
• Mentorship Program: Access development opportunities with the help of experienced professionals.
  
• Employee Wellness: Gympass to keep your health in check and take care of your body.
  
• Culture and Well-being: We foster an environment that values mental health, promotes work-life balance, and encourages connection with our culture.
  

• Technical Expertise: Experience with Edge AI/IoT solutions (relevant for industry), knowledge graphs and ontologies, computer vision, and predictive maintenance or advanced time series analysis.
  
• Business Relevance: Background in industrial or B2B data-driven products.
  
• Innovation: Participation in open innovation, patenting, or contributions to the data/AI community.
  
• Change Management: Leading organizational AI/analytics adoption in complex environments.
  

Mid-Senior level

Full-time

Engineering and Information Technology

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