You will support the design, implementation, and maintenance of cutting-edge data and AI infrastructure, enabling seamless data processing, governance, and integration for Nokia’s next generation products. This is an opportunity to gain hands-on experience with modern data engineering principles while working in a collaborative and innovative environment.

Responsibilities

Platform Development Support:

Assist in implementing dynamic data onboarding processes and maintaining the semantic layer exposed to the data catalog. Contribute to the integration of data governance policies to ensure compliance with regulatory and business requirements.

Data Infrastructure & Compute Pipelines:

Help design and maintain pipelines for real-time and batch data processing, supporting  MLOps and LLM workflow. Collaborate with senior team members to optimize compute environments for hybrid deployments (on-premise and cloud).

Data Lakehouse & Mesh Implementation:

Work on integrating data lakehouse solutions for scalable analytics. Learn and contribute to data mesh principles to enable seamless data combinations for various use cases.

Collaboration & Stakeholder Engagement:

Support senior engineers in collaborating with cross-functional teams, including product management and architecture. Participate in customer engagements to understand and solve industry-specific pai points.

Continuous Delivery & Operational Excellence:

Assist in ensuring continuous delivery (CD) readiness for platform updates and deployments. Contribute to modular and flexible solutions by maintaining clear metadata and content separation.

 

 

Impact

Accountable for quality and accuracy of own output. Responsible for contribution to teamwork. Errors may have impact on function/project/customer. Usually delivers results with a short-term, operational focus and limited impact on others. 

Scope & Contribution

Individual Contributor: Participates as individual contributor to team, usually with limited professional expertise. Makes decisions affecting own work within set parameters, elevates others. Reviews priorities with supervisor. High personal or low collegial interaction. Managerial/Supervisory: May act as Team Leader or Project Leader with some indirect supervisory responsibilities in addition to own work assignments.. Makes decisions that affect own work. 

Innovation

Semi routine tasks of moderate complexity requiring some discretion and judgment. Carries out tasks/activities according to assignment and set guidelines. Moderate degree of supervision and coaching needed. Demonstrates initiative and adaptability to changing business environments. 

Communication

Explains facts, practices, policies, etc. to external and internal parties. Takes actions which respect to the needs and contributions of others and reaches agreement through flexibility and compromise. Manages situations where there is a common desire to reach solution within a team. Sometimes requires ability to influence others outside of own job area on policies, practices and procedures. Builds cross-cultural knowledge and global mindset. 

Key Skills and Experience

Bachelor’s degree in Computer Science, Data Engineering, or related fields (or equivalen work experience). 1-3 years of experience in developing enterprise software, data engineering, cloud platforms, or related field Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and hybrid compute architectures. Basic understanding of data governance, lineage, and quality management. Exposure to MLOps workflows and LLM deployment is a plus Hands-on experience with programming languages like Python, Java, or Go. Familiarity with data processing frameworks (e.g., Apache Spark, Kafka, Flink) is desirable. Excellent communication and collaboration skills with a desire to learn and grow in the telecom AI space.

 

Develop features and perform project tasks in own areas. Responsible for own code quality, review, testing, troubleshooting, debugging activities in own area. Lead development activities of small/medium complexity features. Support peers in completing feature tasks. Feature Owner/Engineer for small/medium complexity features. Participates and contributes to requirements and design review.