Our client, a leader in the financial services industry, is scaling up personalization across multiple business verticals through its Global Digital Marketing function. This group brings together Marketing Technology (Martech), Demand Generation, Marketing Measurement, Marketing Automation, and Personalization to deliver a full-funnel approach that drives connected, personalized customer journeys. The Martech Automation Engineer will play a key role in implementing, optimizing, and maintaining our Customer Data Platform (CDP) and marketing automation tools. You will collaborate with cross functional teams to leverage customer data for strategic decision-making and deliver impactful, personalized experiences at scale.

Key Responsibilities

• Data Architecture: Partner with business leads and data architects to design, implement, and manage end-to-end CDP architecture based on business needs.
• Data Mapping & Integration: Develop XDM schemas for data from sources such as Azure Data Lake, CRM, marketing platforms, and transactional databases.
• Data Pipeline Development: Build and manage end-to-end pipelines for extraction, transformation, and loading of customer data into the CDP.
• ETL Optimization: Continuously improve ETL processes for efficiency, speed, and scalability (real-time and batch).
• Data Transformation: Apply data cleansing, enrichment, and transformation to ensure high-quality, actionable insights.
• Data Quality Assurance: Implement validation rules, testing plans, and monitoring to maintain accuracy and integrity.
• Platform Enhancement: Work with technical leads to identify and implement improvements to CDP integrations and functionalities.
• Technical Documentation: Maintain clear, comprehensive documentation for data processes and configurations.
• Collaboration: Engage with data analysts, business stakeholders, and data scientists to translate requirements into technical solutions.
• Performance Monitoring: Track pipeline performance, troubleshoot issues, and identify optimization opportunities.
• Governance & Compliance: Ensure adherence to data privacy and compliance standards throughout the data lifecycle.

MUST-HAVE SKILLS

• AJO (Adobe Journey Optimizer)
• Marketo
• Salesforce Marketing Cloud (SFMC)
• Journey Optimizer
  (Hands-on experience with these tools is required)

QUALIFICATIONS

• Bachelor’s Degree in Computer Science, Information Technology, or related field (Master’s preferred).
• 5+ years as a Data Engineer with experience in data pipelines and ETL processes.
• Proven experience with Customer Data Platform (CDP) implementations.
• Familiarity with XDM (Experience Data Model) concepts.
• Proficiency in programming languages such as Python, Java, or Scala.
• Hands-on experience with ETL tools, data integration platforms, and data warehousing.
• Knowledge of cloud platforms (Azure, AWS, or GCP) and associated data services.
• Strong understanding of data privacy, governance, and compliance best practices.
• Excellent problem-solving skills and ability to troubleshoot technical issues.
• Strong communication skills to work with both technical and business stakeholders.
• Detail-oriented with a commitment to delivering high-quality work in a fast-paced environment.
  Location: Toronto, ON (Hybrid – 3 days/week in office)
  Duration: 3 months, with strong possibility of extension

• Data Architecture: Partner with business leads and data architects to design, implement, and manage end-to-end CDP architecture based on business needs.
• Data Mapping & Integration: Develop XDM schemas for data from sources such as Azure Data Lake, CRM, marketing platforms, and transactional databases.
• Data Pipeline Development: Build and manage end-to-end pipelines for extraction, transformation, and loading of customer data into the CDP.
• ETL Optimization: Continuously improve ETL processes for efficiency, speed, and scalability (real-time and batch).
• Data Transformation: Apply data cleansing, enrichment, and transformation to ensure high-quality, actionable insights.
• Data Quality Assurance: Implement validation rules, testing plans, and monitoring to maintain accuracy and integrity.
• Platform Enhancement: Work with technical leads to identify and implement improvements to CDP integrations and functionalities.
• Technical Documentation: Maintain clear, comprehensive documentation for data processes and configurations.
• Collaboration: Engage with data analysts, business stakeholders, and data scientists to translate requirements into technical solutions.
• Performance Monitoring: Track pipeline performance, troubleshoot issues, and identify optimization opportunities.
• Governance & Compliance: Ensure adherence to data privacy and compliance standards throughout the data lifecycle