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Sr. Data Engineer

Cineplex Entertainment
Toronto, CAN
Full-time
Hybrid
Discovered 1 weeks ago
Azure DatabricksApache SparkPySparkPythonSQLDelta Lake
Free

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Role overview

Senior Data Engineer responsible for designing and delivering data products that support customer analytics, audience segmentation, personalization, marketing activation, and AI-driven decision-making.

Own and evolve Customer360, Audience360, Braze integrations, and the Databricks Customer Lake.

Work with Analytics, Marketing, Media, Technology, Privacy, and Legal teams on scalable, secure, high-performance data solutions.

Workplace

  • This is a hybrid position requiring three days in the office per week.
  • The office is located at 1303 Yonge Street in Toronto.

Customer intelligence and data products

  • Own the Customer360 roadmap, architecture, delivery, support, and enhancements.
  • Design customer data products integrating identity, preferences, consent, transaction, engagement, and behavioral data.
  • Advance audience segmentation, personalization, activation, and AI-enabled insights.
  • Design and optimize batch and near-real-time pipelines using Azure Databricks, Spark, PySpark, Python, SQL, Delta Lake, Azure Data Factory, and dbt.
  • Build governed data products, reusable frameworks, integrations, and analytical data models.
  • Support Databricks, Braze, and customer engagement integrations for audience activation.
  • Implement monitoring, alerting, data quality controls, incident management, governance, and performance optimization.
  • Lead architecture and code reviews, mentor team members, and manage technical and operational risks.

Requirements

  • Degree or diploma in a related technical field or equivalent practical experience.
  • At least 6 years of data engineering, data platform engineering, or data architecture experience.
  • At least 3 years delivering solutions on Azure Databricks or a similar Spark-based lakehouse platform.
  • Strong SQL, Python, PySpark, Apache Spark, Delta Lake, data modeling, and ETL/ELT experience.
  • Experience with Azure Data Factory, dbt, Git, Azure DevOps, CI/CD, automated testing, and production deployments.
  • Experience with governed data products, secure integrations, data quality, lineage, security, optimization, and operational support.
  • Strong leadership, communication, stakeholder management, mentoring, and collaboration skills.

Preferred qualifications

  • Databricks Data Engineer or Microsoft Azure Data Engineer certification is considered an asset.
  • Customer data platform, Customer360, audience segmentation, personalization, marketing activation, or Braze experience is considered an asset.

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