Software Engineer, Data Core

Who We Are: The 4M story is likely one you haven’t heard before: We are on a mission to unlock access to the world below us, to do for the world below ground what Google Maps did for the world above. By leveraging cutting-edge technology, we are mapping the subsurface infrastructure to make reliable, real-time utility data accessible to the construction industry - completely transforming a traditional industry. We’re a growing startup with 120 employees currently based in Tel Aviv, Israel, and Austin, Texas. The Opportunity We’re looking for an experienced Software Engineer with a strong background to become an integral member of our Data-Core team, tasked with the mission of processing, structuring, and analyzing hundreds of millions of data sources. Your role will be pivotal in creating a unified, up-to-date, and accurate utilities map, services, and applications for accelerating our mapping operations. Your contributions will directly impact our core product's success. Key Responsibilities Build and maintain components within distributed data pipelines — producer-consumer workflows over SQS, Airflow DAGs, Kubernetes-based processing. Integrate outputs from the algorithms and ML teams into production workflows — implementing ETL steps, handling data transformations, ensuring upstream results are consumed correctly. Contribute to shared Python libraries (14 packages consumed by 10+ services) — following existing patterns, writing clean code, understanding how changes affect downstream consumers. Work within stateful workflow engines — implementing new steps, fixing issues in ticket state machines and multi-stage recovery workflows. Debug pipeline issues by tracing data flow through SQS, Airflow, Kubernetes, and PostgreSQL to narrow down where things broke. Contribute to ETL and data infrastructure — multi-source ingestion, taxonomy-based normalization, and database operations. Improve reliability and observability — adding error handling, logging, monitoring, and alerting to existing services.

Requirements: 4+ years as a backend/software engineer with solid Python skills. Experience as a Data Infrastructure Engineer or in a similar role in managing and processing large-scale datasets. Proven experience with AI development tools - we use Claude Code as a daily tool on our team. Experience in deploying a diverse range of cloud-based technologies to support mission-critical projects, including expertise in understanding, testing, and deploying code within a Kubernetes environment. Experience working with message queues (SQS, Kafka, RabbitMQ, or similar) — understands why messages can fail and how to handle errors in a consumer. Familiarity with Airflow (or comparable orchestration) and Kubernetes/Docker in production. Experience with AWS services (SQS, S3) or comparable cloud platforms. Solid PostgreSQL/SQL skills — comfortable writing complex queries, understanding schemas, working with multiple databases. Experience working in a large existing codebase — can read code they didn't write, follow established patterns, and contribute without breaking things. Solid debugging skills — can trace a problem through logs and multiple services rather than guessing at fixes Bachelor’s degree in Computer Science, Engineering or similar (such as equivalent army background). AI-First Mindset  We are building an AI-first engineering culture, and we're looking for engineers who are genuinely excited about working this way. This means you are experimenting with AI tools (code assistants, LLMs) and see AI as a multiplier of your craft. You don't need to arrive with a fully formed AI workflow — but you should have the curiosity and the drive to develop one.