Software Data Engineer (Data Platform)

TL;DR

Software Data Engineer (Data Platform): Designing and building production-grade data services and pipelines to power AI-driven industrial health products with an accent on clean architecture, scalability, and reliability. Focus on implementing idempotent pipelines, lakehouse architectures, and data foundations for AI agents.

Location: Mentions collaboration with teams across Israel and globally

Company

hirify.global is a leader in Machine Health and Process Health solutions, using purpose-built AI technology to help industrial sectors optimize production.

What you will do

• Build and evolve Python-based services and pipelines to ingest industrial events and expose modeled tables and APIs.
• Design idempotent pipelines that handle duplicates, invalid data, and late-arriving events in a reproducible manner.
• Implement incremental aggregations and watermarking strategies for production metrics and operational KPIs.
• Develop lakehouse architectures using Databricks, Delta Lake, and Spark, following Bronze, Silver, and Gold layer patterns.
• Model complex relationships across machines, factories, and sensors to support Digital Twin capabilities and AI agents.
• Partner with global platform and ML teams to ensure high observability, data quality, and system reliability.

Requirements

• Bachelor's degree in Computer Science, Software Engineering, or a related engineering discipline.
• 5+ years of professional software engineering experience building backend or data-intensive systems in production.
• Strong proficiency in Python (modular architecture, testing) and SQL (schema design, indexing, aggregation).
• Hands-on experience with a major cloud platform (Azure, GCP, or AWS) and lakehouse technologies like Databricks or Spark.
• Experience with streaming or messaging platforms such as Kafka, Pub/Sub, or Event Hubs.
• English: Professional proficiency required for collaborating with globally distributed teams.

Nice to have

• Experience with industrial IoT, manufacturing, or operational data platforms.
• Familiarity with Digital Twin architectures and relationship-centric data modeling (Graph databases).
• Exposure to AI/LLM-powered applications, including RAG, agents, and tool calling.

Culture & Benefits

• Stock options.
• Paid parental leave.
• Flex PTO.
• Inclusive, people-first work environment.