This is a high-impact leadership role at the intersection of data engineering, analytics, and AI/ML enablement—ideal for someone who thrives in building high-performance teams and enterprise-grade data platforms that are the backbone of customer-centric innovation. 

• Lead and grow a high-performing global data engineering team focused on eCommerce and Consumer analytics. 

• Architect and oversee the implementation of robust pipelines for clickstream data ingestion, transformation, and enrichment from web, mobile, and digital touchpoints. 

• Partner with analytics, data science, ecommerce engineering and product teams to define reusable, high-quality data products that drive critical KPIs: user engagement, conversion, retention, LTV, churn, etc. 

• Drive the roadmap for real-time event driven and batch processing architectures, enabling rapid experimentation and decision-making. 

• Ensure best practices in data governance, quality, lineage, and observability—across large volumes of consumer and behavioral data. 

• Lead the integration of third-party enrichment sources and identity resolution technologies to build a 360° view of the consumer. 

• Advance platform capabilities that support AI/ML-driven personalization, segmentation, and journey optimization. 

• Champion scalable data architecture aligned with our broader modern data platform strategy. 

• Foster a strong engineering culture that values innovation, quality, speed, and inclusivity. 

• Champion privacy, ethics, and security in data practices to ensure compliance with regulatory standards and foster consumer trust. 

• 10+ years of experience in data engineering, with at least 3–5 years leading high-performing teams in digital commerce or consumer analytics environments. 

• Experienced in software development, CI/CD pipelines, testing, operations, on-call rotation setup, and observability  

• Deep technical expertise in cloud-native data platforms (e.g., GCP, AWS, Azure) and big data frameworks (Spark, Kafka/pub-sub, etc). 

• Proven experience building and scaling clickstream pipelines and digital data infrastructure, ideally using tools like Segment, Adobe/GA4, etc. 

• Experience with customer data platforms (CDPs), identity resolution, and privacy-aware data modeling. 

• Strong command of data warehousing (e.g., BigQuery, Snowflake) and ELT tools (e.g., dbt, Airflow/Kubeflow). 

• Ability to translate ambiguous business goals into actionable data solutions. 

• Familiarity with machine learning pipelines and collaboration with data science teams. 

• Strong cross-functional leadership skills—comfortable aligning with marketing, digital product, engineering, and privacy/legal stakeholders. 

Why Join Us 

You’ll be part of a company investing deeply in data and AI to transform how we serve and understand our customers. You’ll help shape a data ecosystem that delivers precision, personalization, and performance at scale—and lead a team that's at the forefront of redefining how consumer and digital data power growth.