About Us

Our mission is simple—we’re changing the way we care for our parents so they can live safely at home as they age. But how we accomplish our mission is anything but simple. Every day, we’re solving complex problems that don’t come with a playbook. Sound exciting? If you’re someone who shares our core values—Own the Outcome, Solve with Empathy, and Act with Honor—let’s talk.

Founded in 2014, Honor is one of the fastest-growing non-medical home care companies in the U.S. We combine innovative technology with the local, personal touch of our partner agencies to transform a $30B industry that touches millions of families. Our platform powers everything from caregiver operations and workforce management to business intelligence, forecasting, and machine learning.

At Honor, we’re not building technology for technology’s sake. We’re building technology that helps people deliver better care.

The Opportunity

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.

What You'll Do

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.

What We're Looking For

• 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.

Preferred Qualifications

• Strong hands-on experience with Python, Amazon Redshift, AWS-native ETL technologies (including ZeroETL and DMS), Airflow, dbt, Datadog, Fivetran, and AWS CDK.
• Experience designing data governance, metadata, lineage, or self-service data platforms.
• Experience supporting AI, machine learning, or agentic workflow initiatives.
• Experience leading platform modernization efforts in high-growth environments.
• Experience as a Staff Engineer, Principal Engineer, Technical Lead, or Engineering Manager.

What's Next?

Sound like a fit? Apply below!

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