Open Opportunities
Data Automation Engineer
About The Position
About Cellebrite:
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.
The Role:
We are seeking a QA Engineer with a strong passion for data quality, performance, and scale to join our Data Platform team.
This role is ideal for a QA professional who enjoys working close to complex data systems, understands large-scale pipelines, and wants to play a key role in shaping the automation and quality strategy of a data engineering organization.
You will act as the primary quality owner for high-volume, mission-critical data platforms, working closely with data engineers, backend developers, and platform teams.
What You’ll Do:
Data Quality & Validation
- Design and execute data validation strategies for large-scale batch and streaming pipelines
- Ensure data correctness, completeness, freshness, and consistency across the data lake
- Define and automate checks for schema changes, data drift, and data quality regressions
Performance & Scalability Testing
- Plan and execute performance and scalability tests for data pipelines and processing jobs
- Identify bottlenecks across ingestion, transformation, and querying layers
- Partner with engineers to validate performance improvements and prevent regressions
Automation & Infrastructure
- Develop and maintain the data team’s QA automation infrastructure
- Build reusable testing frameworks and tools tailored for large datasets and pipelines
- Integrate automated tests into CI/CD pipelines and production monitoring workflows
Collaboration & Ownership
- Work closely with data engineers, backend developers, and platform engineers throughout the development lifecycle
- Act as the sole QA owner within a cross-functional team, driving quality without becoming a bottleneck
- Participate in design discussions to ensure testability and observability are built in from the start
Quality Mindset & Communication
- Champion a quality-first culture within the team
- Clearly communicate risks, findings, and quality metrics to technical stakeholders
- Balance thoroughness with pragmatism in fast-moving, high-scale environments.
Requirements
Experience:
- Proven experience as a QA Engineer, ideally within data-intensive or platform teams
- Hands-on experience testing large-scale systems, pipelines, or distributed architectures
- Experience working as the sole QA in a cross-functional engineering team.
Technical Skills:
- Strong understanding of data pipelines and data lake concepts
- Experience validating large datasets and implementing data quality checks
- Familiarity with performance and load testing methodologies
- Experience building test automation frameworks (Python preferred)
- Understanding of CI/CD pipelines and automation best practices.
Mindset & Collaboration:
- Passion for data, performance, and technology
- Self-driven, independent, and comfortable owning QA end-to-end
- Strong communication skills and ability to collaborate across disciplines
- Curious, proactive, and eager to learn complex systems.
Nice to Have:
- Experience testing big data or analytics platforms
- Familiarity with cloud environments (AWS preferred)
- Knowledge of Spark, SQL-based analytics, or data processing frameworks
- Experience with data observability or data quality tools.
What We Offer:
- Competitive compensation and benefits
- Opportunity to work on large-scale, mission-critical data systems
- A highly technical, collaborative team environment
- Real ownership and influence over quality and automation strategy
- Continuous learning and professional growth