Berlin • Cybersecurity & AI Startup • Recently Funded

A newly funded cybersecurity startup in Berlin is looking for a Data Engineer to join as a founding team member and help design the core security, identity, and enforcement foundations of a next-generation AI-powered risk management platform.

We are an early-stage startup founded by experienced cybersecurity leaders with backgrounds in Israeli intelligence units.
We are looking for a hands-on Founding Data Engineer for a hybrid role based in central Berlin. If you are passionate about cybersecurity and AI, thrive in fast-paced startup environments, and enjoy building complex platforms from the ground up, this is an opportunity to make a real impact.

We’re building a next-generation cyber risk platform that helps enterprises understand, measure, and reduce identity risk at scale. Our goal is to turn complex identity and security data into clear, actionable risk insights that CISOs and CTOs can trust. You will work from scratch on core platform components from day one, shaping how modern enterprises manage and reason about risk using cloud-native systems, AI-driven analysis, and automated enforcement through AI agents.

Key Responsibilities

Design, build, and operate scalable data pipelines ingesting large volumes of security, identity, and SaaS telemetry data
Develop batch and streaming data processing workflows powering analytics, risk scoring, and AI-driven insights
Build and operate data platforms across cloud-native environments
Own data ingestion from multiple sources including APIs, event streams, and cloud services
Design and maintain data models, schemas, and transformations for analytics and downstream AI workloads
Ensure data quality, consistency, reliability, and observability across pipelines
Optimize data processing performance and infrastructure cost across storage and compute layers
Collaborate closely with backend, AI, and security teams to align data architecture with product needs
Implement monitoring, logging, alerting, and failure handling for data pipelines
Support experimentation, PoCs, and rapid iteration in an early-stage startup environment
Contribute to data security, access control, and compliance readiness
Establish Data best practices as the company scales
Continuously improve platform cost efficiency, reliability, and operational maturity
Decide on Data Tech Stack and build whole Data platform setup from scratch

Must have skills

10+ years of experience in data engineering or data platform roles
5+ years experience with Data Tools on AWS in production environments
Proven experience with design of the Data Warehouse, Data Lake and Lakehouse
Advanced Python skills for data processing and pipeline development
Experience with at least one modern data platform: Databricks, Snowflake, or Amazon Redshift
Strong SQL skills and experience with analytical and operational databases
Experience with Building data topics around AI agents, LLMs, RAG, Embeddings and Vector DBs
Hands-on experience with Kafka for streaming data pipelines
Experience working with as a data lake or primary storage layer
Experience building and operating ETL / ELT pipelines and orchestration at scale(Fivetran, Airflow, AWS Glue, dbt, etc.)
Experience operating data workloads in cloud environments (AWS), AWS S3, AWS Bedrock
Understanding of data quality, validation, and observability practices
Ability to troubleshoot and optimize data pipelines end to end
High ownership mentality, startup mindset, and ability to move quickly.
Experience with PostgreSQL (RDS / Aurora), Neo4J(or similar)
Experience with Coding CoPilots(Claude Code, GitHub Copilot, AWS Whisperer, Codex, etc.)
Knowledge of observability standards (OpenTelemetry, Prometheus)
Experience supporting production SaaS platforms
Ability to build things from scratch at early stage startup
Experience in startup or scale-up environments
Low ego, high commitment, and a true tech startup mentality
Excellent English communication skills

Nice-to-have requirements

Experience with Apache Spark
Experience with real-time streaming architectures and event-driven systems
Exposure to feature stores and ML data pipelines
Knowledge of data security, access control, and encryption
Familiarity with compliance frameworks (ISO 27001, SOC 2, NIS2, DORA)
Experience in cybersecurity, identity, or risk management domains
Interest in security or risk management products

Knowledge of RBAC/ABAC or fine-grained access models
Experience designing permission models, identity graphs, or access control frameworks
Knowledge of Zero Trust principles, least privilege, and continuous verification
Experience with Security related to AI/LLM systems, agent logic, or willingness to learn fast
Previous experience in cybersecurity, identity startups
You are a fan of rock or metal music
German language knowledge

Benefits

Founding Team Member Equity — ESOPs in a well funded cybersecurity company
Competitive Compensation — salary aligned with market, flexible early-stage arrangements possible
Founding Team Member Status — shape the company from day one and own critical data decisions
Fresh Funding Secured — immediate runway to build, hire, and execute fast
Security Contribution — contribute to data architecture across identity, AI agents, and enforcement
High Autonomy — freedom to design and build without corporate overhead
Work with a Technical CEO and CPTO — fast iteration, strong alignment, clear direction
Cutting-Edge Domain — identity security, SaaS-to-SaaS access, AI agent governance
Massive Learning Curve — quickly gain depth in cybersecurity, identity, and AI systems
Fast Career Path — opportunity evolve into leadership as we scale the data team
Berlin Location — top-tier tech environment with strong cybersecurity and AI ecosystems
Direct Impact — your data architecture and code become the foundation of the entire platform
Best Equipment and Tools - High quality equipment and modern tools to help you do your best work from day one
Team Offsites - Regular team offsites designed to build strong connections, alignment, and shared momentum