Senior Engineering Manager, Data Platform
Thales is hiring a Senior Engineering Manager, Data Platform. Level rates it ; you can apply on Thales.
Level's read on this job
- Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include AWS, Kafka and Spark.
- Level classifies it as a senior role.
- Level lists 3,600+ other open roles at Thales.
AI in this role
Lead the data platform engineering team owning pipelines and infrastructure while guiding the development of an emerging AI agent for forensic data investigation.
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 of hands-on engineering experience, including 5+ years managing engineering teams, ideally in a matrixed organization.
Strong background in Data Platform or Big Data engineering within a cloud-native, high-scale environment, with experience designing and operating large-scale, data-intensive systems.
Strong understanding of distributed systems and data platform concepts, including scalability, partitioning, consistency, fault tolerance, performance, and reliability.
Sufficient hands-on technical and coding depth to guide architecture, review designs and code, and troubleshoot complex production issues.
Working knowledge of Java/Spring Boot, Kafka or similar streaming technologies, and Kubernetes.
Solid experience with AWS/Azure/GCP and etc.
Strong experience with PostgreSQL/RDS, OpenSearch/Elasticsearch, and NoSQL databases, including the ability to evaluate architectural trade-offs.
Working knowledge of AI agent architectures and MCP (Model Context Protocol) or similar standards.
Strong communication skills and sound judgment under pressure
Advantages:
Observability tooling; MLOps exposure.
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.
How we rate this
Senior Engineering Manager, Data Platform at Thales rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where engineering management was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, ML Ops, Distributed Systems, Data Engineering, and Engineering Management. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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