CYS_Software Engineer_TP...

Questa posizione è in Leonardo

Il processo di selezione sarà interamente gestito Leonardo.

# Job Description:

Leonardo is an international industrial group, among the world's leading companies in Aerospace, Defense and Security, which creates multi-domain technological capabilities in Helicopters, Aircraft, Aerostructures, Electronics, Cyber Security and Space. With over 60,000 employees worldwide, the company has a solid industrial presence in Italy, the United Kingdom, Poland, the United States, and operates in 150 countries also through controlled companies, joint ventures and shareholdings. A protagonist in the main strategic programs at a global level, it is a technological and industrial partner of Governments, Defense Administrations, Institutions and companies.

Within the **Cyber & Security Solutions Area**, we are looking for a **Software Engineer** for data, cloud and ML services for our Genoa / Rome Laurentina office.

• Below is a list of the main activities foreseen for the role:
• * Develop microservices for data ingestion, transformation, API exposure and processing
• * Implement services for batch and streaming data processing with integration between the two paradigms
• * Develop RESTful, GraphQL and gRPC APIs for data access and analytics query execution
• * Implement services for cloud infrastructure management (compute, storage, networking)
• * Develop services for orchestration and provisioning of cloud resources
• * Implement services for security posture monitoring and compliance checking
• * Develop components for cost tracking, resource optimization and billing
• * Implement services for ML lifecycle management (training, evaluation, deployment, monitoring)
• * Develop services for model registry, versioning and metadata tracking
• * Develop APIs for model serving and inference with support for batch and real-time predictions
• * Implement services for feature store management and feature engineering pipelines
• * Implement services for metadata management and data catalog integration
• * Develop components for data quality validation and monitoring
• * Integrate with data lakehouse for unified batch-streaming storage
• * Integrate with cloud providers APIs (OpenStack, AWS, Azure) for multi-cloud scenarios
• * Implement services for disaster recovery automation and backup orchestration
• * Develop Kubernetes operators for custom resource management
• * Implement caching strategies and query optimization for performance
• * Develop services for data lineage tracking and impact analysis
• * Implement services for model monitoring (drift detection, performance tracking, data quality)
• * Develop services for automated retraining pipelines and continuous learning
• * Ensure scalability, reliability and security for data services, cloud services and ML workloads
• * Implement patterns for fault tolerance, retry mechanisms and error handling
• * Implement testing automation and CI/CD pipelines for cloud services, data services and ML pipelines
• * Maintain high code quality standards through testing and code review
• * Collaborate with data engineers, infrastructure team, data scientists and ML engineers for end-to-end implementation
• ###
• Education

Degree in Computer Engineering, Computer Science or equivalent.

• Seniority
• Expert (2 to 5 years of experience in the role, or more than 5 years of experience in similar roles)
• Technical knowledge and skills
• * Backend development with enterprise languages (Java, Python, Scala, Go) for data platforms, cloud platforms and ML platforms
• * Data processing with modern frameworks (Apache Spark, Apache Flink)
• * Event-driven architectures for data streaming and real-time processing
• * Cloud platforms APIs (OpenStack, AWS/Azure SDKs) and resource management
• * Kubernetes and container orchestration with operators pattern
• * Infrastructure as Code (Terraform, Pulumi) and automation
• * Cloud-native microservices with service mesh integration
• * MLOps practices for model lifecycle automation
• * Model serving frameworks (TensorFlow Serving, TorchServe, Triton Inference Server)
• * ML orchestration tools (Kubeflow, MLflow) and experiment tracking
• * Feature stores (Feast, Tecton) and feature engineering pipelines
• * API development (RESTful, GraphQL, gRPC) for data services, infrastructure services and ML services
• * Relational and NoSQL databases optimized for analytics (columnar, document, wide-column)
• * Data lakehouse integration (Delta Lake, Apache Iceberg) with ACID semantics
• * Security automation (policy enforcement, compliance scanning, secrets management)
• * Distributed caching (Redis, Memcached) for performance optimization
• * API design for infrastructure services and ML services with versioning and backward compatibility
• Behavioral skills
• * Autonomy in managing complex multi-component tasks
• * Good communication skills and analytical problem solving
• * Orientation towards code quality, data quality, automation, infrastructure as code, performance and scalability
• * Security mindset for cloud environments
• * Effective collaboration in cross-functional teams (backend, data engineering, analytics, infrastructure, ML)
• * Proactivity in knowledge sharing and continuous improvement
• Language skills
• Native Italian, Professional English (B2)
• Computer skills
• * Backend languages (Java, Python, Scala, Go) and frameworks (Spring Boot, FastAPI)
• * Apache Spark (PySpark, Scala) for distributed data processing
• * Apache Flink for stream processing (DataStream API, Table API)
• * Event streaming (Apache Kafka) and message brokers
• * Cloud platforms (OpenStack, integration with AWS/Azure)
• * Advanced Kubernetes (operators, CRDs, admission controllers, GPU support with NVIDIA GPU Operator)
• * Infrastructure as Code (Terraform, Ansible, Pulumi)
• * ML frameworks (TensorFlow, PyTorch) and model formats (ONNX, SavedModel)
• * Model serving (TensorFlow Serving, TorchServe, Triton)
• * MLOps tools (Kubeflow, MLflow, DVC)
• * Feature stores (Feast) and data versioning
• * Containerization (Docker) and deployment on Kubernetes
• * Relational databases (PostgreSQL), NoSQL (MongoDB, Cassandra), columnar (ClickHouse), time-series (TimescaleDB)
• * Data lakehouse platforms (Delta Lake, Apache Iceberg)
• * Distributed cache (Redis) and query optimization
• * Security tools (Vault, OPA, Falco) for cloud security
• * API design and versioning strategies
• * CI/CD pipelines and monitoring (Prometheus, Grafana) for data applications, cloud services and ML systems
• ###
• Other
• * Willingness to travel nationally for short periods
• * Experience with large-scale big data processing, cloud infrastructure projects, ML/AI projects is a plus
• * Data engineering (Databricks, Snowflake), cloud (AWS/Azure, OpenStack, Kubernetes), streaming (Confluent Certified Developer for Apache Kafka, Flink) certifications are preferred qualifications
• * Knowledge of data warehousing, OLAP, data modeling, analytics, ML algorithms, data science is a plus
• * Background in data-intensive projects, system administration, SRE, distributed systems or high-performance computing is a plus
• * Availability to obtain security clearance
• **Seniority:** Expert
• **Primary Location:** IT - Genova - Fiumara
• **Additional Locations:** IT - Roma - Via Laurentina
• **Contract Type:** Permanent
• **Total Base Pay Range:** 36k-50k
• **Hybrid Working:** Hybrid

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