Senior Backend & Data Engineer (AWS)

TL;DR

Senior Backend & Data Engineer (AWS): Design and build large-scale, high-performance data platforms and backend services powering cloud-based digital investigation products with an accent on batch and streaming ETL/ELT pipelines using Spark, Glue, and Athena. Focus on optimizing performance, reliability, observability, and ensuring security/compliance in distributed cloud-native environments.

Location: Petah Tikva, Israel

Company

hirify.global’s AI-powered Digital Investigation Platform enables public safety organizations and intelligence agencies to access, analyze, and share digital evidence via cloud, on-premises, and hybrid deployments.

What you will do

• Design, develop, and maintain scalable, secure data platforms and backend services on AWS.
• Build batch and streaming ETL/ELT pipelines using Spark, Glue, Athena, Iceberg, Lambda, and EKS.
• Develop backend components and data-processing workflows in cloud-native environments.
• Optimize performance, reliability, and observability of data pipelines and backend services.
• Collaborate with Data Science, ML, DevOps, and Product teams to deliver data-powered solutions.
• Drive best practices, code quality, technical excellence, security, compliance, and auditability.

Requirements

• 8+ years of experience in Data Engineering and/or Backend Development in AWS-based, cloud-native environments.
• Strong hands-on experience writing Spark jobs (PySpark) and running workloads on EMR and/or Glue.
• Proven ability to design and implement scalable backend services and data pipelines.
• Deep understanding of data modeling, data quality, pipeline optimization, and distributed systems.
• Experience with Infrastructure as Code and automated deployment of data infrastructure.
• Strong debugging, testing, and performance-tuning skills in agile environments.
• High level of ownership, curiosity, and problem-solving mindset.

Nice to have

• AWS certifications (Solutions Architect, Data Engineer).
• Experience with ML pipelines or AI-driven analytics.
• Familiarity with data governance, self-service data platforms, or data mesh architectures.
• Experience with PostgreSQL, DynamoDB, MongoDB.
• Experience building or consuming high-scale APIs.
• Background in multi-threaded or distributed system development.
• Domain experience in cybersecurity, law enforcement, or regulated industries.