• Define partner onboarding and clean room architecture patterns across Snowflake, LiveRamp, and Databricks that are secure, scalable, and repeatable • Configure and manage partner-specific clean room environments; deploy and manage Python-based libraries within the platform ecosystem • Establish and maintain MLOps practices, including model serving, monitoring, and pipeline orchestration for AI/ML features deployed within the platform ecosystem • Own design and enforcement of granular RBAC policies and least-privilege service accounts • Serve as the technical lead for onboarding new partners, implementing privacy-preserving controls (e.g., aggregation thresholds and anonymization techniques) • Design, build, and operate scalable ELT pipelines using Snowpark and/or PySpark and advanced SQL to provision Gold datasets • Implement and evolve identity resolution logic mapping internal data to 3P identifiers (including LUIDs, RampIDs, TransUnion IDs), ensuring privacy-safe practices • Design and operate scalable data architectures across Snowflake and Databricks supporting batch and near real-time processing patterns • Build robust automated checks (e.g., Great Expectations or custom SQL assertions) and define quality standards to detect schema drift, null rate spikes, and volume anomalies • Lead performance optimization across platforms (query tuning, caching, incremental processing) and define and implement query tagging and chargeback models for accurate cost attribution • Establish monitoring, alerting, runbooks, and standard operating procedures to improve platform reliability and reduce incident time-to-resolution • Validate that output data adheres to privacy and business requirements, and define test strategies for partner-facing releases • Serve as the escalation point for diagnosing connection failures, data discrepancies, or latency issues with partner technical teams • Design and build internal AI agents (using frameworks like LangChain, Snowflake Cortex) and mentor other engineers through code reviews, design discussions, and operational best practices

• Title: Senior Data Engineer • Location: Remote • Duration: C2H • Salary: 1-2Lkhs Per Month

• Lead teams of software engineers to improve the lives of Henry Schein One users and their patients through the creation of market-leading solutions • Help recruit, develop, and retain engineers to create a high-performing team • Oversee team leaders and support them in fulfilling their mission and delivery commitments • Enable engineering teams to practice continuous delivery at scale by identifying and removing workflow roadblocks • Inspire, motivate and coach to enable continuous development of team leaders and their teams • Ensure products are secure, compliant and reliable for Henry Schein One customers • Collaborate with senior leaders on the vision and strategy for workstreams and products • Partner closely with Product leadership to influence and understand the strategic commitments of your teams • Build strong cross-functional relationships and influence others to pursue the best possible user experience • Enable process and practice maturity to deliver on global growth opportunities • Positively and collaboratively influence decision-making to improve practices across your teams, department, and stakeholder network • Travel typically up to 10% of time • Office environment with no special physical demands required

• Define the architectural backbone and scalability of Holafly’s entire data ecosystem. • Ensure global operations are fueled by high-quality, real-time insights. • Bridge the gap between infrastructure and analytics, enabling data-driven decision-making. • Design and evolve a world-class data architecture that scales seamlessly with rapid global expansion. • Establish engineering excellence by implementing robust CI/CD practices and version control for all data pipelines. • Ensure data reliability and security across all platforms, supporting mission-critical ML models and business analytics. • Drive strategic technology choices, selecting the best tools and cloud platforms to maintain a competitive edge. • Cultivate high-performing squads, mentoring data engineers to deliver efficient, automated ETL/ELT solutions. • Partner with cross-functional leaders to translate complex business requirements into scalable technical realities.