Principal Data Engineer

Readyon.ai

Job Location:

San Francisco, CA - USA

Monthly Salary: Not Disclosed

Posted on: Yesterday

Vacancies: 1 Vacancy

Department:

Engineering

Job Summary

Transform How Frontline Work Runs

Enterprises struggle to manage hundreds of millions of dollars in frontline labor spend due to decades-old software and manual processes creating massive avoidable costs. Frontline labor often represents 40% of the P&L yet the systems managing this $3 trillion market were built for static schedules and limited flexibility.

ReadyOn was founded to reject that paradigm. Staffing is not a scheduling problem; it is a real-time supplydemand orchestration problem. ReadyOn is an AI-native labor operating system built from the ground up for AI agents to perform real-time labor optimization - much like ridesharing platforms that match drivers and riders in real time but applied to frontline labor instead of fixed one-size-fits-all schedules.

Whos Building It

AI is not a bolt-on feature in our platform. Every decision from demand forecasting to shift assignment flows through an adaptive autonomous decision layer that learns from operational data and continuously optimizes for cost compliance and worker satisfaction. Behind that system is a founding team of experts in labor markets enterprise software and AI-enabled platforms:

Reza Engineering leader who scaled enterprise systems at Google Yahoo and AT&T

Dominic Operator who optimized labor-intensive operations in 21 countries

Mohammad Stanford professor and leading expert in algorithmic market design

ReadyOn has already proven productmarket fit with multiple multi-million-dollar customers consistent expansion within existing accounts and measurable ROI that moves stock prices.

Hands-On Builders Leading AI Innovation

Were building a top-tier engineering team to reimagine how labor is managed at scale. As a Principal Data Engineer you will own the data platform and core data services that power ReadyOns real-time labor operating system enabling AI agents to orchestrate frontline work across thousands of shifts locations and workers every day.

Ideal candidates

Are hands-on senior engineers who thrive in ambiguous high-impact environments and naturally set technical direction for others.
Care deeply about clean system design scalability and elegant architecture across both data and backend systems and are not afraid to rethink default patterns.
Enjoy working closely with product design and AI research teams to deliver new data-driven experiences customers actually use.
Focus on business outcomes not just technical output and love solving real business problems with data services and automation.

Responsibilities

Design build and scale data pipelines and data services using Python TypeScript Apache Airflow PySpark AWS Glue and Snowflake to support both real-time and batch workloads.
Design operationalize and monitor ingest and transformation workflows including DAGs alerting retries SLAs and robust data quality checks for production environments.
Collaborate with AI platform and backend teams to automate ingestion data validation and real-time compute workflows and drive the roadmap toward a production-grade feature store that supports AI agents and decisioning.
Partner closely with the core engineering team to shape ReadyOns Integration Platform ensuring external systems (HCM WFM payroll timekeeping and other enterprise tools) integrate cleanly and are observable end to end in ReadyOn dashboards.
Model data structures and implement efficient scalable transformations in Snowflake and PostgreSQL including schema design indexing partitioning and query optimization for high-volume low-latency use cases.
Build reusable frameworks connectors and internal libraries that standardize how data is published discovered and consumed by backend services analytics and AI workloads.
Implement and continuously improve observability across pipelines and services: structured logging metrics tracing data quality monitoring lineage and incident response playbooks.
Provide technical leadership on data and backend integration: participate in system design and code reviews mentor other engineers and help drive sound pragmatic technical decisions in a fast-moving environment.

Your background

5 plus years of production data engineering experience including owning critical pipelines datasets and services in live environments.
Deep hands-on experience with Apache Airflow AWS Glue PySpark and Python-based data pipelines including orchestration monitoring and troubleshooting at scale.
Solid SQL skills and experience working with PostgreSQL in production: schema design query optimization migration management and handling concurrency in large-scale environments.
Strong understanding of cloud-native data and service workflows (AWS preferred) including data warehousing storage security and cost-efficient architectures.
Fluency in TypeScript and experience with a backend framework such as NestJS (or other frameworks) including designing decoupled services and robust enterprise interfaces; GraphQL experience is a significant plus.
Experience implementing observability for data and backend systems: logging metrics tracing data validation and automated alerts for pipeline and service health.
Comfortable collaborating with AI/ML and data science teams understanding how data flows into models feature stores and real-time decisioning workflows even if you are not a data scientist yourself.
Bonus: hands-on experience with conflict resolution in collaborative or concurrent-editing systems graph processing feature stores or real-time coordination tools and algorithms.

If youre looking for predictability rigid structure or narrow specialization this probably isnt the right role. This is a principal-level position for hands-on builders who want to define the data foundation of an AI-native labor operating system and shape how data AI and backend services come together in production.

Interview Process

Screening call with Talent (Recruiter)
1:1 interview with Founder/CTO Reza Iranmanesh (hiring manager)
Technical panel: cross-functional technical interview (virtual)
Onsite interview with direct team and select founding members

Location: Why In-Person Matters

As a high-growth startup tackling complex industry-defining challenges in-person collaboration is essential to our success. Being together in our San Francisco office enables rapid decision-making creative problem-solving and strong team trust critical in this formative phase. Youll be required to work onsite Monday through Friday to help shape our culture accelerate learning and build the foundational technology that will define ReadyOns future.

Compensation

Final compensation will be determined based on your skills experience and geographic addition to salary this role may include comprehensive benefits bonuses commissions and a meaningful equity stake in ReadyOn.

Potential Recruitment Fraud Memo

Recruiting at ReadyOn is handled directly by our in-house team or verified hiring partners. We will never request payment bank details or confidential personal information during our recruitment process. If you are contacted by someone claiming to represent ReadyOn and you are concerned about the legitimacy of the interaction please contact us at to verify any communication.

EEO Statement

ReadyOn is committed to building a diverse and inclusive workplace. We are proud to be an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race color religion gender gender identity or expression sexual orientation national origin genetics disability age or veteran status.

Required Experience:

Staff IC

Transform How Frontline Work RunsEnterprises struggle to manage hundreds of millions of dollars in frontline labor spend due to decades-old software and manual processes creating massive avoidable costs. Frontline labor often represents 40% of the P&L yet the systems managing this $3 trillion market...