Python developer állások III. kerületben (programozó, fejlesztő)

• Active partnership with sales and project managers to estimate, design, develop and deliver solutions
• Continuous communication with domain experts and product owners to understand core business needs and goals to synthesize requirement and quality standards

• Leading and mentoring a team of ML engineers
• Owning model quality end-to-end from experimentation to production-ready artifacts
• Conducting regular 1-on-1s for career development and feedback
• Driving task prioritization, sprint planning, and resource allocation

• Use formal verification algorithms to formally prove the correctness of complicated logic problems
• Identify key behaviors for verification to write clear testplans for complex designs
• Implement testplans using innovative formal techniques
• Drive tools to realize their best performance

• Support Meridian technical due diligence and transition readiness using AI-assisted software engineering methods
• Analyse OpenStack-style services and surrounding components to map APIs, configuration flows, service dependencies, database usage, and operational assumptions

• Strengthening Meridian software handover readiness by combining AI-assisted software engineering with code quality, security validation, dependency analysis, and build evidence generation for complex cloud platform repositories
• Trustworthy validation of large codebases

• Building and operating Kubernetes platforms on Open Telekom Cloud
• Managing Infrastructure as Code with Terraform and Terragrunt
• Implementing GitOps delivery using ArgoCD
• Operating PostgreSQL and Apache Kafka on Kubernetes
• Integrating security controls into CI/CD pipelines

• Active involvement in the software design and test of reference application processor firmware
• Low level software development, test and debug on various platforms including software models, development boards and shipping products

Shaping and evolving the architecture of MDO network automation capabilities including reusable automation patterns, interfaces and technical guidelines...

• Design and development of low-level software to integrate new Arm architecture features across Linux, Android, and related userspace components
• Architecture, development, and optimization of core OS subsystems with a focus on performance, power efficiency, and security

• Building AI-powered automation for complex cloud engineering environments
• Combining platform engineering, software development and cloud expertise with modern Generative AI technologies to automate parts of the software development lifecycle

• Data pipeline development
• Data integration
• Data warehousing
• Data modelling
• Data quality and governance
• Performance optimization
• Collaboration with data scientists and analysts
• Technology selection
• Security and compliance
• Monitoring and troubleshooting

• Design and implement automation for storage provisioning, capacity management, and operational workflows using Python, Bash, and IaC tooling
• Drive reduction of manual toil through scripted workflows and self-service enablement

• Design, deploy, and manage scalable cloud and hybrid infrastructure environments with a primary focus on automation, reliability, and security
• Build and maintain Infrastructure-as-Code solutions using Terraform and other automation tools to provision and manage AWS and on-premises resources

• Design and implement cloud security controls across AWS, Azure, and GCP
• Build security automation using CI/CD pipelines, Infrastructure as Code, and Policy as Code
• Develop automated compliance checks and remediation workflows

• Technical leadership post-sales for strategic customers in big data project design and implementation
• Identification and driving of new initiatives to turn data into actionable business value aligned with business goals

• Implementation and improvement of business objects for mobile network infrastructure in backend systems up to the API layer
• Development and maintenance of business objects including data models, backend logic, and APIs

• Skálázható cloud-native adatarchitektúrák tervezése Databricks vagy MS Fabric platformokra
• Adatmodellek, sémák és tárolási minták kialakítása (lakehouse, Delta, Parquet)
• Batch és streaming adatok betöltési pipeline-jainak megtervezése
• ETL/ELT folyamatok és transzformációs stratégia meghatározása

• Technical leadership and mentoring of data engineers
• Technical oversight for Databricks solutions
• Design and implementation of scalable ETL/ELT pipelines using Databricks, Python/PySpark, SQL, and Delta Lake

• Csapatmunkában történő részvétel jó minőségű, hatékony üzleti alkalmazások létrehozásában
• A rendszertervezéssel kapcsolatos egyeztetési és dokumentációs feladatok ellátása
• Komponensek működési céljainak meghatározása, valamint a kimeneti követelmények és formátumok értékelése

• Design and development of innovative AI solutions
• Collaboration with global technologists, data scientists, and industry experts
• Development of scalable data pipelines
• Building software products and services from the ground up
• Assessment of data landscapes and ensuring data quality