Software Data Engineer, Data Platform

You are a Software Data Engineer with deep experience building data-intensive systems, not a traditional ETL or BI-focused Data Engineer. In this role, you will design and build production-grade data services, platforms, and pipelines that power DIH and our AI-driven products. You will combine strong software engineering fundamentals with modern data engineering practices, with a focus on clean architecture, reliability, scalability, observability, and testing.As a Software Data Engineer, Data Platform, you will:Build and evolve Python-based services and pipelines that ingest raw industrial events, store them reliably, and expose clean, well-modeled tables and APIs for downstream consumers, including Digital Twin, Smart Canvas, AI agents, and analytics.Design systems that handle duplicates, invalid data, late-arriving events, and reprocessing in a principled, incremental, and reproducible manner.Collaborate with platform, machine learning, and product teams across Israel and globally to transform complex data challenges into robust, observable, and scalable software solutions.Requirements: What You BringBachelor's degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or a related engineering discipline, or equivalent practical experience.5+ years of professional software engineering experience, including substantial experience building backend systems, distributed systems, or data-intensive applications in production environments.Strong Python engineering skills, including modular architecture, dependency management, testing practices, observability, and production-grade code quality.Strong SQL and data modeling expertise, including schema design, indexing strategies, event-driven data models, and scalable analytical aggregations.Hands-on experience building incremental and idempotent data pipelines that handle duplicate, invalid, and late-arriving events without impacting downstream consumers.Experience with at least one major cloud platform (Azure, GCP, or AWS) and modern lakehouse technologies such as Databricks, Delta Lake, Spark, or equivalent architectures.Experience with streaming or messaging technologies such as Kafka, Pub/Sub, Event Hubs, or similar event-driven systems.Proven ability to diagnose and resolve production data issues, including data quality problems, schema evolution, backfills, replay scenarios, and performance bottlenecks.Strong written and verbal communication skills in English and experience collaborating effectively with globally distributed teams.Nice to HaveExperience building industrial, IoT, manufacturing, or operational data platforms.Familiarity with Digital Twin architectures and industrial data models.Experience with graph databases, context graphs, knowledge graphs, or relationship-centric data modeling.Exposure to AI/LLM-powered applications, including retrieval-augmented generation (RAG), agents, tool calling, or evaluation frameworks.Experience working with Databricks or similar lakehouse platforms from both application and platform perspectives.Experience building data products that directly support AI agents, intelligent applications, or machine learning workflows.This position is open to all candidates.