> Markdown version of [/jobs/ext/503472-data-engineer](https://www.wearedevelopers.com/jobs/ext/503472-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** READYON, INC. - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $140,000.0 - $230,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Code Review, Data as a Services, Directed Acyclic Graph (Directed Graphs), Data Validation, Data Infrastructure, Data Structures, Data Warehousing, Python (Programming Language), PostgreSQL, Node.Js, Operational Databases, Query Optimization, Cloud Services, Standard Sql, Data Streaming, TypeScript, Data Logging, Snowflake, Indexer, Backend, Pyspark, Low Latency, AWS Glue, Data Analytics, Graphql, NestJS, Data Pipelines - **Published:** June 4, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=15705014fe84a21e ## About the Role Do you have experience in TypeScript?, * 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., * 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 Node.js 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 you're looking for predictability, rigid structure, or narrow specialization, this probably isn't 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. ## Description * 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 ReadyOn's 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Streaming AI Responses in Real-Time with SSE in Next.js & NestJS](https://www.wearedevelopers.com/videos/1630-streaming-ai-responses-in-real-time-with-sse-in-next-js-nestjs) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)