At Thales, we know technology has the ability to make our world more secure, sustainable, and inclusive – and that it’s all driven by human intelligence.
Because it takes human intelligence to build and power the systems and solutions that people depend on every day. So we stay curious and make space for diverse points of view. We share what we know and we challenge what’s possible.
We’re driving progress in some of the world’s most important industries - from the bottom of the oceans to the depths of space and cyberspace - and from manufacturing to engineering, we work together to build a future we can all trust.
Imperva, a Thales company, is a globally recognized cybersecurity leader, dedicated to securing data and applications across diverse environments. Our cutting-edge solutions empower organizations to safeguard their most critical assets, ensuring robust protection against emerging threats.
Imperva, a Thales company, protects the world's largest organizations from cyberattacks. Our Platform Engineering group builds the foundation and developer experience powering Imperva's application security products.
We're looking for a Senior Engineering Manager to lead our Data Platform group — owning the pipelines, storage, and streaming infrastructure, deployed on AWS, that power data-driven capabilities across the company, including an emerging AI agent for forensic data investigation.
Key Responsibilities:
- Own end-to-end delivery for the group — roadmap, execution, and Agile/SAFe process.
- Hire, mentor, and grow a team of engineers.
- Guide architecture and technical direction for scalable data pipelines (real-time and batch), streaming (Kafka), and processing frameworks (Spark/Flink).
- Oversee the platform's AWS infrastructure and cloud architecture decisions.
- Ensure sound data storage design across relational, NoSQL, and search systems.
- Drive improvements in reliability, observability, and cost efficiency.
- Guide the team's development of an AI agent for forensic use cases, including MCP tool design for safe, effective data access.
- Represent the group across a matrixed org and partner with product teams.
Requirements :
- 10+ years hands-on engineering experience, including 5+ years managing engineering teams, ideally in a matrixed org.
- Background in backend, data, or platform engineering in a cloud-native environment, with enough depth to guide technical decisions.
- Working knowledge of Java/Spring Boot, Kafka or similar, and Kubernetes.
- Solid experience with AWS, as the platform is deployed on AWS.
- Understanding of distributed systems concepts (scalability, fault tolerance, consistency).
- Familiarity with data storage tech (PostgreSQL/RDS, OpenSearch/Elasticsearch, NoSQL).
- Working knowledge of AI agent architectures and MCP (Model Context Protocol) or similar standards.
- Strong communication skills and sound judgment under pressure.
Advantages:
- Big data frameworks (Spark, Flink, Presto), orchestration tools (Airflow).
- Event-driven architecture and data modeling experience.
- Observability tooling; MLOps exposure.
- Multi-region/large-scale cloud experience.
- Hands-on experience building AI agents or MCP servers.
Thales, champions inclusion and we believe diversity strengthens the fabric of our culture. We are an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, colour, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.
Skills Required
- 10+ years hands-on engineering experience, including 5+ years managing engineering teams
- Experience in a matrixed organization
- Background in backend, data, or platform engineering in a cloud-native environment
- Working knowledge of Java and Spring Boot
- Working knowledge of Kafka or similar streaming platforms
- Working knowledge of Kubernetes
- Solid experience with AWS
- Understanding of distributed systems concepts (scalability, fault tolerance, consistency)
- Familiarity with data storage technologies (PostgreSQL/RDS, OpenSearch/Elasticsearch, NoSQL)
- Working knowledge of AI agent architectures and MCP (Model Context Protocol) or similar standards
- Big data frameworks (Spark, Flink, Presto)
- Orchestration tools (Airflow)
- Event-driven architecture and data modeling experience
- Observability tooling and MLOps exposure
- Multi-region/large-scale cloud experience
- Hands-on experience building AI agents or MCP servers
- Strong communication skills and sound judgment under pressure
Thales Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Thales and has not been reviewed or approved by Thales.
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Retirement Support — Retirement plans with employer contributions and matches, profit sharing, and share purchase opportunities are emphasized across multiple regions. These elements are positioned as competitive components of total rewards.
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Leave & Time Off Breadth — Generous PTO that increases with tenure, paid holidays, and paid military, maternity, and paternity leave are described. This breadth supports work–life balance across locations.
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Flexible Benefits — Hybrid work options, flexible schedules, and parental supports such as childcare benefits and leave for sick children are available in several markets. Flexibility is presented as a core part of the employee experience.
Thales Insights
What We Do
Thales is a global high technology leader investing in digital and “deep tech” innovations – connectivity, big data, artificial intelligence, cybersecurity and quantum technology – to build a future we can all trust, which is vital to the development of our societies. The company provides solutions, services and products that help its customers – businesses, organisations and states – in the defence, aeronautics, space, transportation and digital identity and security markets to fulfil their critical missions, by placing humans at the heart of the decision-making process.








