Senior Software Engineer / Data Platform Engineer (Databricks, Graph, APIs)

About

The team sits within the network technology organisation and is responsible for building advanced data platforms that support digital twin capabilities across the access network. The group combines network design data, telemetry, mapping technologies, and graph intelligence to improve troubleshooting, planning, operational efficiency, and market competitiveness.

The team works on highly scalable engineering products including large data pipelines, graph databases, APIs, and mapping platforms. Their work enables smarter network decisions, faster fault resolution, and better use of operational resources.

This is a technically strong team focused on solving complex real-world problems using modern engineering and data technologies.

Responsibilities

• Design, build, and maintain scalable ETL / ELT pipelines processing large enterprise datasets.
• Develop robust data products within Databricks and Spark environments.
• Build configurable ingestion frameworks and multi-environment deployment pipelines.
• Engineer APIs that expose network intelligence products to internal users and systems.
• Work with graph databases such as Neo4j to model relationships across network assets, devices, and telemetry.
• Improve data quality, exception handling, and pipeline resilience across multiple data sources.
• Write production-grade software with strong engineering standards, testing, and automation.
• Collaborate with technical teams to translate complex operational problems into scalable engineering solutions.
• Help evolve digital twin and next-generation network intelligence platforms.

Skills & Experience

Required

• Strong software engineering background (Python preferred).
• Experience building production systems and scalable backend applications.
• ETL / ELT pipeline engineering experience.
• Experience with Spark, Databricks, or similar distributed data platforms.
• API development experience (REST / backend services).
• Strong problem-solving skills and ability to work with complex data.

Preferred

• Neo4j or graph database experience.
• Experience with Airflow, AWS EMR, or similar orchestration/data tools.
• Telecom, infrastructure, or network data experience.
• CI/CD and DevOps engineering practices.
• Experience handling large, imperfect enterprise datasets.

Ideal Candidate

A strong software engineer with an interest in data engineering, or a data engineer with excellent coding discipline. Candidates with transferable adjacent skills are highly valued over exact tool matching alone.