Senior Data Engineer – Corporate Data Analytics

This is a fully remote position, open to applicants in Canada.

📋 Description

• Design, develop, and maintain scalable cloud-native data pipelines that cater to batch and near-real-time applications.

• Engineer and enhance data ingestion, transformation, and orchestration pipelines utilizing Azure Data Factory, Microsoft Fabric, Databricks, and associated services.

• Implement and sustain lakehouse and medallion architectures (bronze, silver, gold) to facilitate analytics and AI workloads.

• Create robust transformation logic using SQL, PySpark, and Python with an emphasis on performance and maintainability.

• Collaborate with Analytics/BI Engineers to ensure datasets are tailored for semantic layers and AI consumption.

• Work alongside data scientists to assist with feature engineering and model training efforts.

• Establish data quality, validation, lineage, and observability solutions to maintain trust in data assets.

• Design and enforce data security measures, including access controls, encryption, and data classification.

• Automate deployment and operational processes using DataOps and infrastructure-as-code methodologies.

• Create and update technical documentation, runbooks, and architecture diagrams.

• Provide technical guidance and mentorship to junior data engineers.

⛳️ Requirements

• Legally authorized to work in Canada.

• Capable of obtaining Government of Canada Reliability or Secret security clearance.

• Proficient in English (speaking, reading, writing).

• Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or a related discipline.

• Strong comprehension of lakehouse, data warehouse, and medallion architecture patterns.

• Over 8 years of pertinent professional experience, which includes 5+ years in cloud data engineering or data platform roles.

• More than 5 years of practical experience with Microsoft Azure data services.

• At least 5 years of experience in building data pipelines using SQL and Python or PySpark, working with structured and semi-structured data.

• Experience collaborating with analytics, BI, and AI teams.

🏝️ Benefits

• Health, medical, and life insurance benefits.

• Defined contribution pension plan with company matching.