Senior Data Platform Engineer (Databricks)

Location: Tel Aviv, Israel; hybrid with 3 days per week in the office

Company

hirify.global builds AI-first products and operates shared data infrastructure for its data and R&D teams.

What you will do

• Build, operate, and own large-scale batch and streaming data pipelines in production.
• Administer and evolve Databricks, including Unity Catalog, compute, governance, job and cluster tuning, and cost management.
• Operate Confluent Kafka, CDC pipelines, Airflow, Elasticsearch, databases, S3, and the underlying Kubernetes platform.
• Improve reliability, performance, observability, testing, documentation, and cost tagging across the shared data platform.
• Drive architecture decisions across Databricks, Kafka, Elasticsearch, and AWS.
• Build self-service platform tooling and integrate AI coding tools, LLMs, MCP servers, embeddings, vector search, and agent interfaces into real workflows.

Requirements

• 5+ years of hands-on experience building and operating large-scale batch and streaming data pipelines in production.
• Deep experience with Spark and Databricks, including Delta Lake, Unity Catalog, cluster tuning, Structured Streaming, or DLT.
• Experience with Kafka, CDC, Debezium or equivalent tools, schema evolution, and failure-mode analysis.
• Experience writing and operating Airflow DAGs, with expert Python and SQL skills.
• Strong data modeling and architecture judgment, including scale, performance, and cost tradeoffs.
• Experience with AWS, Terraform, Docker, Kubernetes, CI/CD, and leading cross-team technical initiatives end to end; daily use of AI coding tools and production LLM or agent tooling is required.

Nice to have

• Elasticsearch operations at scale, including indexing pipelines, reindexing, and rollout strategies.
• FinOps or cloud cost management experience for data platforms.
• Vault or similar secrets management and advanced Kubernetes operations.
• Experience inheriting systems with technical debt and making them reliable and maintainable.

Culture & Benefits

• Builder-oriented engineering culture focused on turning ambiguous ideas into shipped systems.
• Hybrid work model with three office days each week.
• Ownership of infrastructure used across data and R&D teams.
• Emphasis on automation, reliability, governance, cost efficiency, and operational simplicity.