Lead level Data Engineer

Responsibilities

• Design, build, and maintain scalable ingestion pipelines from priority source systems into Bronze, Silver, and Gold layers of the Medallion architecture, covering both batch and incremental load patterns.
• Complete source-to-target mapping documentation, agree conformed dimensions, taxonomies, and systems of record with the governance workstream, and implement the Gold aggregation layer with KPI metric definitions signed off by business stakeholders.
• Model and transform business data across the Medallion layers into structures that support operational Power BI reporting, ensuring Silver and Gold layer tables are optimised for the agreed KPI and reporting requirements.
• Apply and maintain governed data access controls in the chosen cloud data platform, including role-based permissions and any column-level or row-level security required to meet PIPEDA compliance obligations as defined by the governance workstream.
• Implement robust ingestion, transformation, and data quality processes including automated DQ checks across all Medallion layers, error handling for failed pipeline runs, and end-to-end testing from source systems to the Gold layer.
• Drive Silver-to-Gold reconciliation sign-off with business stakeholders, ensuring a single agreed definition for every committed KPI and eliminating cross-department reporting discrepancies.
• Complete and maintain the data dictionary for all platform tables, ensuring data is well-documented, accessible, and aligned to business definitions used by BI developers, report authors, and stakeholders during UAT.
• Work with architects and client data stakeholders to align designs with enterprise data standards, governance requirements, and long-term maintainability.
• Produce data engineering runbooks and handover documentation, including pipeline operational guides and technical documentation structured for the client's internal team to maintain and extend the platform independently.
• Support deployment of data solutions into controlled Dev, Test, and Production environments.
• Support continued development of the Medallion architecture in later phases, including additional Bronze, Silver, and Gold datasets, and contribute to pipeline orchestration running reliably on the agreed ingestion schedule.
• Strong hands-on experience with SQL and Python for data processing and transformation.
• Experience building scalable data pipelines and transformation workflows for large, complex datasets.
• Strong understanding of data modelling, semantic layer design, and analytical data structures.
• Experience with Azure data services, including Azure Data Factory for orchestration and ingestion (including Self-Hosted Integration Runtimes for on-premises connectivity) and Azure Data Lake Storage as a landing zone.
• Hands-on experience with Snowflake, including building transformation notebooks or jobs, managing compute, and working within a Medallion or equivalent layered architecture.
• Experience working with large analytical, transactional, or domain-rich enterprise datasets is highly desirable.
• Understanding of governed data access patterns, role-based permissions, and compliance controls, including familiarity with PIPEDA or equivalent Canadian data privacy requirements and how these translate into platform-level access design.
• Familiarity with testing, validation, and monitoring for data quality and reliability.
• Experience with Git-based CI/CD development workflows.
• Strong communication skills and ability to work collaboratively with technical and business stakeholders.

Requirements

• Familiarity with Power BI semantic model design and how Gold layer table structures, naming conventions, and relationships affect downstream report development and performance.
• Specific experience with Databricks (Unity Catalog, Repos, Delta Live Tables) or Snowflake (Streams, Tasks, Snowpipe) is a strong advantage.
• Experience working in regulated enterprise environments, ideally in telecommunications or similarly complex data landscapes, with an understanding of data sensitivity classification and PII handling requirements.
• Experience contributing to knowledge transfer and internal capability e

Additional Information

We are looking for an experienced Senior Data Engineer to support the delivery of a foundational Azure data platform for a large telecommunications client. This role will be central to building and operating the ingestion pipelines, Medallion architecture, and data models that underpin operational reporting across the business. The ideal candidate will have strong hands-on experience in cloud data engineering, pipeline development, data modelling, and working with modern cloud data warehousing platform, whether Databricks or Snowflake. This person will work closely with BI Consultants, DevOps Engineers, and Data Governance leads to ensure that data from priority source systems is reliably ingested, transformed, and delivered as trusted, well-governed datasets that support business decision-making and PIPEDA compliance.

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Company Intel

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