CYS_Software Engineer_TP
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
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