Engineer Manager Data & Analytics

at  Yalo Inc

YALO

Hi! This is Yalo! We are on a mission to bring conversational commerce to the world…
Remember how it used to be to interact with businesses that knew and understood you, that could recommend exactly what you needed, and that with a simple message could get you what you wanted??? Yep… neither do we. That is why at Yalo we are marrying the scale of digital commerce with the personalization and simplicity of conversations to help companies delight their users.
We know that traditional SAAS companies focus on first world problems… we don’t! Having started in Latin America, our roots are in Emerging Markets and therefore we care about bringing amazing experiences to a population that traditionally has been underserved, such as the small shop owner in Brazil that is ordering online for the first time.
If you’re looking for a place to make things happen, learn fast, and impact emerging markets in a way that hasn’t been done before, look no further.
Come Join us in our mission of improving billions of lives through the power of conversational commerce!

JOB REQUIREMENTS (MUST HAVE)

• Experience: Minimum of 12-15 years in data engineering, analytics, and machine learning, with at least 5 years in a leadership role. Proven experience in managing large-scale data projects and leading cross-functional teams.
• Technical Expertise: Deep knowledge of big data technologies (e.g., Hadoop, Spark, Kafka), data engineering practices, and cloud platforms (e.g., AWS, GCP). Strong proficiency in machine learning frameworks and tools, including Python, TensorFlow, and MLOps platforms.
• Leadership Skills: Demonstrated ability to lead and inspire teams, manage multiple projects simultaneously, and drive results in a fast-paced environment.
• Strategic Vision: Ability to develop and execute a strategic data plan that drives business value. Strong analytical thinking and problem-solving skills, with a focus on delivering measurable outcomes.
• Communication and Collaboration: Excellent communication skills, with the ability to translate complex technical concepts into clear, actionable insights for non-technical stakeholders.
• Education: Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field. Advanced degree (e.g., Master’s, Ph.D.) preferred.

• Leadership and Team Management: Lead, mentor, and develop a high-performance team of data engineers, data scientists, and machine learning professionals. Foster a collaborative and innovative environment that encourages continuous learning and growth.
• Strategic Data and Analytics Leadership: Develop and execute a comprehensive data strategy that aligns with organizational goals. Oversee the design, implementation, and optimization of big data architectures, data lakes, and real-time data processing pipelines.
• Machine Learning and AI Development: Drive the development, deployment, and optimization of machine learning models and AI-driven solutions. Ensure that machine learning initiatives are integrated with business processes to enhance decision-making and operational efficiency.
• Cross-functional Collaboration: Work closely with business units and senior leadership to identify data needs, prioritize projects, and deliver insights that support strategic objectives. Champion data-driven decision-making across the organization.
• Data Governance and Compliance: Implement robust data governance frameworks to ensure data quality, security, and compliance with relevant regulations (e.g., GDPR, SOC 2). Oversee the management of data privacy and security protocols.
• Innovation and Continuous Improvement: Stay abreast of industry trends and emerging technologies in data, analytics, and machine learning. Lead initiatives to explore new tools, techniques, and methodologies that can enhance our data capabilities.
• Project Management and Execution: Oversee the successful delivery of data and analytics projects, ensuring they are completed on time, within scope, and aligned with business objectives. Manage resources effectively to maximize project outcomes.