Director - Data Engineering & Analytics

Job Summary

We are seeking a visionary and accomplished engineering leader to serve as the Director of Data Engineering and Analytics. This role will oversee multiple Data Engineering and Analytics teams organized along product lines, that design, build and deploy data products. Central to this body of work is the Platform Engineering team responsible for a cloud-based Data Platform, that serves as the foundation for developing and deploying all data products. The Data Platform also serves as the foundation for developing and deploying all AI products.

You will collaborate closely with Platform Engineering, Data Product Management, AI/ML, and Operations to deliver scalable, reliable, and high-quality data solutions that power our business decisions and AI products.

Responsibilities

• Provide strategic and operational leadership for Data Engineering and Analytics teams to build data products, pipelines, and solutions that enable business intelligence, analytics, and AI/ML use cases

• Oversee the development and deployment of scalable ETL/ELT pipelines, data marts, and analytics models that meet enterprise data needs

• Ensure effective use of the generic frameworks, tools, and platforms to build, test, and deploy data solutions efficiently

• Partner closely with peers to align on capabilities, enhancements, and optimizations needed for ingestion, transformation, orchestration, and deployment frameworks

• Drive a data product mindset, ensuring that data assets are well-architected, high quality, governed, and reusable across the organization

• Foster collaboration with Data Product Management, AI/ML teams, and business stakeholders to prioritize and deliver high-impact data solutions

• Build and scale a high-performing team through recruitment, coaching, and mentoring, promoting a culture of innovation, inclusion, and continuous learning

• Proven experience in leading large, distributed teams , managing organizational change, and scaling engineering functions

• Lead transformational initiatives to modernize data architecture, adopt emerging technologies, and evolve engineering practices

• Cultivate a collaborative and transparent culture , breaking down silos and aligning cross-functional teams around shared goals

• Define clear objectives, KPIs, and performance metrics for teams, and provide feedback to ensure accountability and growth

• Focus on automation, efficiency, and quality, while meeting or exceeding delivery timelines

• Ensure adherence to data governance, privacy, and security policies in all data engineering and analytics work

• Represent Data Engineering and Analytics in cross-functional forums, advocating for best practices, innovation, and alignment with enterprise architecture

Qualifications

• 15+ years of experience in data engineering, analytics, and technology leadership roles, with demonstrated success in delivering enterprise data solutions

• Strong software/data engineering background, having started as an individual contributor and grown into senior leadership roles

• Proven experience in leading large, distributed teams , managing organizational change, and scaling engineering functions

• Expertise in building ETL/ELT pipelines, data warehouses, data marts, and analytics products on top of cloud-native platforms (GCP, AWS, or Azure)

• Experience in SQL, Python, and one or more programming languages (Java, Scala, Go, etc.)

• Deep understanding of data modeling, data computation frameworks, distributed systems, and big data architectures

• Experience in working with frameworks and automation tools provided by shared services teams

• Proficiency in Agile methodologies, DevOps/CI-CD principles, and data governance best practices

• Strong collaboration skills with the ability to partner across engineering, product, and business functions

• Excellent communication and stakeholder management skills; ability to represent the function internally and externally

• Bachelors, Masters, or PhD degree in Computer Science, Engineering, or a related field

Preferred Qualifications

• Experience delivering analytics self-service capabilities, conversational analytics and enterprise dashboards using BI tools (e.g., Looker, Power BI, Tableau)

• Familiarity with AI/ML operationalization, including enabling data pipelines for AI/ML model development and deployment

• Knowledge of data mesh principles or federated data architectures

• Experience with cost optimization and cloud resource management for data workloads.

• Demonstrated ability to inspire and influence at all levels of the organization, from engineers to executives

What You Bring

• Passion for building data engineering and analytics solutions that enable scalability, trust, and business impact

• A transformational leadership style that motivates teams to embrace change, challenge the status quo, and deliver breakthrough results

• A people-first mindset , with a strong focus on team development, empowerment, and well-being

• A strategic vision for the future of data and analytics, coupled with the operational rigor to execute at scale