{bc}
oracle

Senior AI Data Engineer

Nokia
IND
Full-time
Senior
Hybrid
Discovered 2 days ago
PythonKubernetesCommunicationAzurePower BI

Full Job Posting

Qualifications

  • You have:
  • Strong hands-on experience in production-grade data and software engineering.
  • Strong Python skills and experience designing automated data pipelines.
  • Experience with distributed data processing, data modelling, metadata and data quality.
  • Experience with PostgreSQL, Elasticsearch or comparable data and search technologies.
  • Cloud-native engineering, Kubernetes and container experience.
  • Knowledge of CI/CD, monitoring and production operations.
  • Ability to translate complex or ambiguous requirements into scalable technical solutions.
  • Strong ownership, collaboration and communication skills, with the ability to guide other engineers while remaining hands-on.
  • It would be nice if you also had:
  • Experience with Microsoft Azure and Microsoft Fabric.
  • Experience with Spark, BigQuery, OLAP or similar data and analytics technologies.
  • Experience with LLM-assisted data processing, embeddings, vector search or semantic retrieval.
  • Knowledge of knowledge graphs, linked data or semantic-data architectures.
  • Experience with Power BI, Apache Superset or similar visualization tools.
  • Familiarity with 3GPP, O-RAN, Wi-Fi, MPEG, JVET or ITU-R data.
  • Experience with research, standardization, intellectual property or patenting-related data and use cases.

Responsibilities

  • Own data solutions from requirements and architecture through deployment, operation and continuous improvement.
  • Build scalable ingestion, transformation and processing pipelines for standards and strategic datasets.
  • Transform complex information into structured, reliable and AI-ready data assets.
  • Develop AI/LLM-assisted data processing, semantic ingestion and retrieval capabilities.
  • Strengthen metadata, data quality, lineage, freshness, observability and reliability.
  • Develop and operate solutions using Python, Kubernetes, Spark, PostgreSQL, Elasticsearch and Microsoft Fabric.
  • Enable AI, LLM and agentic applications through high-quality data and knowledge services.
  • Provide technical guidance and knowledge sharing while remaining hands-on in solution delivery.

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