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Data Architect

2 months ago

Toronto, Ontario, Canada Pacific Data Integrators Full time
About the Role

Pacific Data Integrators is seeking a highly skilled Data Engineer to join our team. As a Data Engineer, you will play a critical role in supporting our client's OCM Self-serve platform.

Key Responsibilities
  • Technical Operationalization: Design, implement, and maintain data pipelines deployed to our client's investment entities, ensuring high levels of reliability, scalability, and security.
  • Business Relationship Building: Foster a business relationship that assists in meeting business demands, working closely with stakeholders to understand requirements and deliver solutions.
  • ETL/ELT Pipeline Deployment: Deploy ETL/ELT pipelines to achieve high levels of reliability, scalability, and security, sourcing, transforming, and delivering structured and unstructured assets for analytical use.
  • Performance Optimization: Optimize performance of ETL pipelines and data sources, ensuring efficient data processing and delivery.
  • Solution Build and Delivery: Participate in solution build, delivery, support, and troubleshooting, working collaboratively with cross-functional teams.
  • Azure Resource Management: Provision and manage Azure resources, including security and cost, ensuring optimal resource utilization and cost-effectiveness.
  • Pipeline Monitoring and Improvement: Monitor pipelines, improve reliability, and automate audit processes, ensuring data quality and integrity.
  • Technical Test Planning and Execution: Define and execute technical test plans, performing unit, performance, and integration tests, and automating regression tests.
  • Agile Development Environment: Operate in an Agile development environment, collaborating with teams to deliver high-quality solutions.
  • Effective Communication: Communicate effectively with engineers, product managers, data and business analysts, IT infrastructure specialists, security specialists, enterprise architects, and senior management.
  • Change Leadership: Lead change and communicate impacts to partners and fellow team members, ensuring seamless transition and adoption.
  • Process Improvement: Identify, define, and implement opportunities for improving existing processes, ensuring continuous improvement and efficiency.
  • Project Management: Work on multiple projects simultaneously, ensuring timely delivery and meeting business demands.
  • Data Management Practices: Participate in establishing sound data management practices for the team and the organization, ensuring data quality and integrity.
  • Infrastructure Development: Help shape and scale the future of our development and production infrastructure, ensuring alignment with business objectives.
Requirements
  • Professional Experience: 3+ years of experience solving sophisticated technical data projects using the Microsoft Azure data stack or equivalent work experience, preferably in the financial industry.
  • Education: Bachelor's degree in a scientific or engineering field of study or equivalent work experience.
  • Certifications: Microsoft Data Engineer Associate level certificate is considered an asset.
  • Industry Knowledge: Industry knowledge of best practices, previous experience in developing and deploying operational procedures, tuning guides, and best practices documentation.
  • Relationship Building: Consistent track record of building deep technical relationships, experience in aligning expectations across various partners.
  • Problem-Solving: Ability to trace data lineage/workflows and resolve technical issues with minimal direction.
  • Teamwork: Motivated and keen to work in a collaborative environment with a focus on team success.
Preferred Skills
  • Enterprise-scale Technical Experience: Experience with cloud and hybrid infrastructures, architecture designs, and technology management.
  • Python Experience: Experience in handling data in Python using libraries like Pandas, Numpy.
  • SQL Proficiency: Proficient with SQL.
  • Data Architecture: Experience with data architecture, modeling, data warehousing.
  • Azure Data Platform: Breadth of technical experience and knowledge across the Azure Data Platform, with depth/subject matter expertise in two or more of the following Data Platform resources: Azure Databricks, Azure Functions and/or Web Apps using C#.Net, Azure Managed SQL Server, Azure Data Factory.
  • CI/CD Pipeline Automation: Proven experience automating CI/CD pipelines using Azure DevOps or equivalent work experience.
  • Containerization: Experience with containerization and container deployment to Kubernetes.
  • Star Schema Reporting: Experience developing star schema reporting pipelines using Kimball or Data Vault v2.0 methodologies.