Senior Data Engineer

Experience Level: intermediate to senior (Strong technical experience required)

We are supporting a large-scale broadband and network services organization undergoing a major transformation of its network intelligence and billing platforms
. The company operates multiple on-prem data centers with GPU and CPU stacks and processes extremely high volumes of telemetry and usage data from network devices.

This role sits at the intersection of data engineering, infrastructure, and real-time systems
, supporting a multi-year $25M billing system replacement and broader network modernization initiatives.

The Senior Data Engineer will be deeply hands-on, owning Kafka-based pipelines and ELT workflows that ingest, process, and persist high-volume streaming data. This is not a reporting or analytics-only role — it’s focused on building and operating resilient data infrastructure at scale.

• Direct report to a Data Engineering / Network Intelligence Team Lead
• Dotted-line relationship to the Head of Data / Network Intelligence

• Design, build, and operate Kafka-based streaming pipelines ingesting data from network meters and devices
• Own end-to-end ELT pipelines for billing and network intelligence use cases
• Aggregate, process, and store high-volume telemetry and KPI data across on-prem infrastructure
• Work with Spark (PySpark) for large-scale data processing where appropriate
• Develop and maintain SQL-based data models for downstream consumption
• Orchestrate workflows using Airflow
• Package, deploy, and operate services using Docker and Kubernetes
• Work closely with data science and network intelligence teams to ensure data accuracy, availability, and performance
• Support ongoing modernization efforts while maintaining reliability of production systems
• Troubleshoot performance, scaling, and reliability issues in high-throughput environments

Core Technologies (Must-Have):

• Python (strong, production-level experience)
• Spark / Py Spark
• SQL
• Docker & Kubernetes (ability to deploy and manage services independently)
• Modern on-prem infrastructure (not cloud-native, but cloud-like tooling)
• High-volume, high-throughput data streams (Databricks is not viable due to scale)

• 3+ years of strong, hands-on data engineering experience
• Proven experience building and operating streaming data pipelines at scale
• Comfortable working close to infrastructure and production systems
• Able to work independently and “push results” without heavy oversight
• Experience in telecom or networking is nice-to-have
  , but not required
• Strong problem-solving mindset; pragmatic and execution-focused

This role IS:

• Highly hands-on and execution-driven
• Focused on real-time data, infrastructure, and scale
• Critical to a major billing and platform transformation

This role is NOT:

• A purely analytics or BI-focused position
• A cloud-only / Databricks-heavy environment
• A junior or learning-role — strong experience is required

• High impact on core revenue and network systems
• Modern tooling with real engineering challenges
• Strong compensation flexibility for the right candidate
• Remote-friendly within Canada (preffering alignment with EST hours)