Edge-to-Cloud Data Engineer for Autonomous Labs

The Ellison Institute Of Technology (eit)

Oxford

Hybrid

GBP 65,000 - 95,000

Full time

14 days+

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Benefits offered by this job

Enhanced holiday
Pension 7.5%
Life Assurance
Income Protection
Private Medical Insurance
Cycle to Work
Nursery Salary Sacrifice
Electric car scheme
Employee discounts
Coaching & Therapy

Job summary

The Ellison Institute Of Technology (EIT) in Oxford is seeking an experienced Data Engineer to join the Scientific Compute and Data team. You will build the data layer for autonomous systems, handling edge-to-cloud ingestion, streaming, and knowledge graph construction to support AI research and robotics workflows.

You will work with Python-based data pipelines, Kafka, MQTT, and APIs, collaborating with researchers, software engineers, and domain scientists to ensure data quality, provenance,

Qualifications

  • Strong programming experience in Python and data engineering.
  • Experience building high-throughput data ingestion pipelines.
  • Knowledge of edge-to-cloud architectures and streaming systems.

Responsibilities

  • Build high-throughput, low-latency ingestion for live data streams from edge to cloud.
  • Work across the edge-to-cloud stack including MQTT, Kafka, storage and APIs.
  • Turn streams into structured transactions and build a knowledge graph for traceability.
  • Collaborate with AI researchers and software/robotics teams to ensure data quality and lineage.

Skills

Python
SQL
Kafka
MQTT
Edge-to-cloud
System design
Collaboration

Tools

MQTT
Kafka
FastAPI
GraphQL
gRPC

Job description

The Ellison Institute Of Technology (EIT) in Oxford is seeking an experienced Data Engineer to join the Scientific Compute and Data team. You will build the data layer for autonomous systems, handling edge-to-cloud ingestion, streaming, and knowledge graph construction to support AI research and robotics workflows.

You will work with Python-based data pipelines, Kafka, MQTT, and APIs, collaborating with researchers, software engineers, and domain scientists to ensure data quality, provenance,

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