Senior Data Engineer

Company Overview:

Cellebrite’s (Nasdaq: CLBT) mission is to enable its global customers to protect and save lives by enhancing digital investigations and intelligence gathering to accelerate justice in communities around the world.

Cellebrite’s AI-powered Digital Investigation Platform enables customers to lawfully access, collect, analyze and share digital evidence in legally sanctioned investigations while preserving data privacy. Thousands of public safety organizations, intelligence agencies and businesses rely on Cellebrite’s digital forensic and investigative solutions-available via cloud, on-premises and hybrid deployments-to close cases faster and safeguard communities.

To learn more, visit us at www.cellebrite.com, https://investors.cellebrite.com/investors and find us on social media @Cellebrite.

Position Overview:

Cellebrite is seeking a Senior Backend & Data Engineer to join its SaaS Data Platform team.

This role offers a unique opportunity to design and build large-scale, high-performance data platforms and backend services that power Cellebrite’s cloud-based products.

You will own features end to end-from architecture and design through development and production deployment-while working closely with Data Science, Machine Learning, DevOps, and Product teams.

What You’ll 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 a cloud-native environment.
• Optimize performance, reliability, and observability of data pipelines and backend services.
• Collaborate with ML, backend, DevOps, and product teams to deliver data-powered solutions.
• Drive best practices, code quality, and technical excellence within the team.
• Ensure security, compliance, and auditability using AWS best practices (IAM, encryption, auditing).
  
  

• AWS Services: S3, Lambda, Glue, Step Functions, Kinesis, Athena, EMR, Airflow, Iceberg, EKS, SNS/SQS, EventBridge
• Languages: Python (Node.js/TypeScript a plus)
• Data & Processing: batch & streaming pipelines, distributed computing, serverless architectures, big data workflows
• Tooling: CI/CD, GitHub, IaC (Terraform/CDK/SAM), containerized environments, Kubernetes
• Observability: CloudWatch, Splunk, Grafana, Datadog
  
  

• Design, develop, and maintain scalable, secure backend services and data platforms on AWS
• Build and operate batch and streaming ETL/ELT pipelines using Spark, Glue, Athena, Iceberg, Lambda, and EKS
• Develop backend components and data processing workflows in a cloud-native environment
• Optimize performance, reliability, and observability of data pipelines and backend services
• Collaborate with ML, backend, DevOps, and product teams to deliver data-driven solutions
• Lead best practices in code quality, architecture, and technical excellence
• Ensure security, compliance, and auditability using AWS best practices (IAM, encryption, auditing)
  
  

• 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.
  
  

• 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 other regulated industries.