Principal Data Engineer

Xplore Inc•Markham, ON

About The Position

This role is for an experienced technical leader to lead the technical roadmap and upskill the Xplore data engineering team. You will define the end-to-end data platform (ingestion, storage, modeling, governance, quality, observability), unify data currently siloed across on-prem network/OSS/BSS systems, Salesforce CRM, and other business sources, and embed compliance, lineage, and cataloging by design.

Requirements

10+ years of data engineering experience, including 4+ years leading platform or team-level initiatives.
Expert hands-on skills with modern data lakehouse and distributed compute platforms (e.g., Spark-based ecosystems, cloud-native storage, streaming frameworks).
Strong experience with enterprise data cataloging, lineage, and governance at scale.
Proficiency in Python and/or Scala, advanced SQL, and performance tuning for large-scale ELT.
Practical knowledge of ingestion from Salesforce, on-prem RDBMS, files/telemetry, and APIs; experience bridging on-prem systems with cloud platforms.
Solid grasp of security and privacy controls (RBAC, encryption, tokenization/masking), and familiarity with Canadian privacy regimes (PIPEDA/CPPA, Law 25) and other relevant standards.
Experience with CI/CD, infrastructure as code, automated testing frameworks, and data observability solutions.
Comfort collaborating across domains (Network, Care, Marketing, Finance, Sales) and translating business needs into scalable data products.
Advanced academic background in a quantitative discipline such as Computer Science, Engineering, Mathematics, or a related field.
Excellent communication skills, a coaching mindset, and the ability to set platform vision and deliver iteratively.

Responsibilities

Own the architecture and delivery of a scalable enterprise lakehouse platform following the medallion pattern (bronze/silver/gold layers) to support BI, data science, and AI use cases.
Stand up robust ingestion pipelines from on-prem and cloud systems (e.g., SQL Server/Oracle, network telemetry/OSS, Salesforce via APIs/CDC), enabling both batch and streaming workloads.
Implement governance, security, and compliance controls end-to-end: role-based and attribute-based access control, row/column-level security, secrets and key management, data retention, and privacy-by-design aligned to Canadian regulations (e.g., PIPEDA/CPPA, Quebec Law 25) and other relevant standards.
Establish enterprise data lineage and cataloging using modern metadata management and data discovery tools; curate business glossaries and data contracts with domain owners.
Define data quality SLAs/SLOs and automated validation at ingestion and transformation stages; implement observability and alerting for freshness, volume, and schema drift.
Partner with analytics, data science, and AI/ML teams to provision clean, well-documented datasets and features, and enable MLOps-friendly patterns.
Lead engineering best practices: CI/CD, infrastructure as code, cost governance, performance tuning, and FinOps reporting (tracking and optimizing cloud/data platform spend).
Create reference architectures, standards, and reusable frameworks; mentor data engineers and champion engineering excellence and security-first development.
Collaborate across information security, privacy, legal, and compliance domains to translate policies into technical controls, and to support audits and evidence collection.
Engage with business stakeholders to prioritize the roadmap, translate use cases into data products, and measure value delivered.
Build, mentor, and inspire a high-performing data engineering team; establish best practices for reproducibility, testing, and documentation