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.
  
  

• 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).