Staff Data Platform Engineer, Honor

• 8–10+ years of experience building and operating large-scale data platforms, pipelines, and warehouses in cloud environments, with deep expertise in AWS
• Proven track record leading complex technical initiatives and influencing architecture across teams
• Strong software engineering fundamentals and experience building production-grade systems
• Deep expertise in modern data warehousing, ELT/ETL architectures, and data platform design
• Experience operating data platforms with a focus on reliability, observability, data quality, and cost optimization
• Proven ability to leverage modern AI-assisted and agentic development tools to architect, build, and operate production-grade systems
• Experience partnering with data scientists, analysts, product managers, and software engineers to deliver business impact
• Demonstrated ability to navigate ambiguity, drive alignment, and lead through influence rather than authority
• Passion for building platforms that empower others and scale organizational impact

Desirable

• We’re looking for a Staff Data Engineer to help shape the future of Honor’s data platform
• This role is focused on building the foundational data platform that powers analytics, machine learning, operational decision-making, and emerging AI capabilities across Honor. As a senior technical leader, you will define architecture, drive platform strategy, and lead the implementation of scalable systems that make trusted data accessible across the organization
• This is an opportunity to join at a pivotal point in our evolution. We are modernizing our data platform, investing in cloud-native AWS services, and building the governance and data access capabilities needed to support the next generation of AI-powered and agentic workflows. You'll tackle complex technical challenges, influence company-wide architecture decisions, and help define how data is consumed across the business
• You'll tackle complex technical challenges, influence company-wide architecture decisions, and help define how data is consumed across the business
• Build and Evolve Our AWS-Native Data Platform
• Lead the architecture and development of scalable, secure, and cost-efficient data platforms on AWS
• Architect and optimize our Data Warehouse to support growing analytical, operational, and AI-driven workloads
• Define and implement Infrastructure-as-Code standards using AWS CDK
• Own Data Orchestration and Data Engineering Foundations
• Design and operate scalable orchestration frameworks using Airflow and FiveTran
• Partner with the Data Analytics team to establish data modeling standards and transformation practices using dbt
• Build reusable, maintainable data pipelines and workflows that enable rapid development and reliable operation
• Enable Trusted Data Access Through Governance and AI Readiness
• Establish governance, metadata, lineage, and access patterns that make data discoverable, trustworthy, and easy to use
• Help define how both employees and AI-powered systems safely access and leverage company data
• Build the foundations that enable self-service analytics and future agentic workflows across the organization
• Drive Reliability, Observability, and Operational Excellence
• Establish monitoring, alerting, and observability standards using Datadog and modern platform engineering practices
• Build scalable data quality frameworks that ensure confidence in business-critical data
• Continuously improve platform reliability, performance, and cloud cost efficiency
• Lead Through Technical Influence and Partnership
• Partner closely with Data Science, Analytics, Product, and Engineering teams to solve complex business problems through data
• Provide technical leadership, architectural guidance, and mentorship across the data organization
• Influence long-term platform strategy and engineering best practices across multiple teams