What you will do:Job Summary Reporting to the Director, Data Engineering, the Senior Data Engineer will play a key role in designing and delivering the data products that power customer analytics, audience segmentation, personalization, marketing activation, and AI-driven decision-making.
In this role, you will own and evolve critical customer data platforms and products, including Customer360, Audience360, Braze integrations, and our Databricks Customer Lake. You will work closely with teams across Analytics, Marketing, Media, Technology, Privacy, and Legal to transform complex business needs into scalable, secure, and high-performance data solutions.
This is an opportunity for a hands-on technical leader who enjoys building modern data products from the ground up while driving operational excellence and continuous improvement. Beyond the Customer Intelligence domain, you will also contribute to broader enterprise data initiatives and help shape the future of Cineplex's data platform ecosystem.
This is a hybrid position (3 days in the office per week). Office location is 1303 Yonge Street, Toronto.
Key ResponsibilitiesCustomer Intelligence Platform & Data Product Ownership
- Serve as the technical lead and owner for Customer360, driving roadmap planning, architecture, delivery, support, and ongoing enhancements.
- Design and maintain customer data products that bring together identity, preferences, consent, transaction, engagement, and behavioral data.
- Collaborate with business and technology stakeholders to prioritize initiatives, define requirements, and deliver measurable business value.
- Advance our customer intelligence capabilities, including audience segmentation, personalization, activation, and AI-enabled insights.
Enterprise Data Engineering & Architecture
- Design, build, test, and optimize scalable batch and near real-time data pipelines using Azure Databricks, Spark, PySpark, Python, SQL, Delta Lake, Azure Data Factory, and dbt.
- Build trusted, production-ready data products using modern lakehouse architecture and best practices.
- Develop reusable frameworks, components, and integration patterns that improve engineering efficiency and scalability.
- Create robust analytical and dimensional data models that support reporting, self-service analytics, machine learning, and AI use cases.
Audience Segmentation & Activation
- Own and support data integrations between Databricks, Braze, and other customer engagement platforms.
- Design reliable and secure pipelines that enable audience activation across marketing, advertising, personalization, and media channels.
- Implement scalable integration patterns including API connectivity, incremental processing, schema evolution, monitoring, and data reconciliation.
- Partner with Marketing and Media teams to enable audience creation, campaign activation, measurement, and future Marketing360 capabilities.
Reliability, Governance & Optimization
- Ensure the reliability and performance of customer data products through monitoring, alerting, data quality controls, incident management, and continuous improvement practices.
- Implement and support data governance standards using Unity Catalog, including access controls, lineage, auditing, and data ownership.
- Ensure customer data solutions meet privacy, security, consent, and regulatory requirements.
- Continuously optimize Databricks workloads and infrastructure to improve performance, scalability, and cost efficiency.
Technical Leadership & Collaboration
- Lead architecture discussions, design reviews, code reviews, and technical problem-solving across the Data Engineering team.
- Mentor team members and champion engineering best practices across coding, testing, CI/CD, governance, and support.
- Support and provide coverage across Cineplex's broader data ecosystem, including Customer360, Media360, Operations360, and shared data platforms.
- Identify and proactively manage technical, operational, quality, security, and delivery risks
Requirements - Degree or diploma in Computer Science, Software Engineering, Information Systems, Data Analytics, or a related field, or equivalent practical experience.
- Databricks Data Engineer and/or Microsoft Azure Data Engineer certification is considered an asset.
- 6+ years of experience in data engineering, data platform engineering, or data architecture, including ownership of production data solutions.
- 3+ years of hands-on experience delivering solutions on Azure Databricks or a similar Spark-based lakehouse platform.
- Strong expertise in SQL, Python, PySpark, Apache Spark, Delta Lake, data modelling, and modern ETL/ELT development practices.
- Hands-on experience with Azure Databricks, Azure Data Factory, dbt, Git, Azure DevOps, CI/CD pipelines, automated testing, and production deployments.
- Experience building scalable, governed data products and pipelines, with a strong understanding of data quality, lineage, security, performance optimization, and operational support.
- Experience designing and supporting secure integrations across APIs, SaaS platforms, databases, and cloud-based data ecosystems.
- Ability to translate complex business requirements into scalable, reliable, and business-ready data solutions.
- Experience with customer data platforms, Customer360 solutions, audience segmentation, personalization, marketing activation, Braze, or related customer intelligence technologies is considered an asset.
- Strong leadership, communication, stakeholder management, mentoring, and cross-functional collaboration skills.
This position is a current vacancy and is being actively recruited to fill an existing role within the organization.While we appreciate all interest, only those candidates selected for an interview will be contacted. Wage ($):$85,000 - $115,000CAD
