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.
Key responsibilities include:- 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
The ideal candidate will possess:- 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.
Condition of Employment:As a condition of employment and in order to comply with industry related data security standards, this position is subject to the successful completion of a Criminal Background Check. Details will be supplied to applicants as they move through the selection process.
