One of our clients is looking for a Cloud Data Architect works directly with clients to understand their challenges and designs practical cloud based solutions in Google Cloud and similar private cloud environments. Combining hands on data engineering, analytics modeling, and client problem solving, this role ensures data is usable, insights are trusted, and marketing and business teams, such as paid media, CRM/lifecycle, and growth teams, can make informed decisions with confidence around campaign performance, customer acquisition, and retention.The successful candidate will act as a trusted technical advisor, helping clients navigate complex data challenges while delivering practical, production ready solutions.Primary ResponsibilitiesLead technical discovery sessions with clients to understand business challenges, define solution approaches, and recommend cloud data architectures that meet functional and strategic objectivesIntegrate data from marketing platforms (e.G., paid media, analytics, CRM) and apply domain knowledge to frame business problems and deliver insights aligned with marketing performance objectivesCollaborate directly with clients to understand business objectives, technical requirements, and success criteriaServe as a trusted technical advisor and partner to clients, guiding them through solution design decisions, implementation approaches, trade offs and best practices and supporting long term successNavigate ambiguous and evolving requirements by structuring problems, validating assumptions, and aligning technical solutions to real business needs without relying on incomplete or incorrect inputsAct as the conduit between client business,



marketing and their technical teams to ensure alignment from technical problem definition through deliveryDevelop data integration for customer private cloud environments, leveraging available tools in that platform, APIs, and scriptingBuild, or consult on, infrastructure required for optimal extraction, transformation, and loading of data across diverse data sourcesAssess existing customer pipelines and offer improvements for efficiency, security, scalability and data qualityMentor and support team members through technical guidance and knowledge sharing to help elevate team capabilities and promote best practicesDevelop reusable data models, pipelines, and dashboard templates that improve delivery consistency and accelerate future client engagementsUnderstand cloud infrastructure and operational requirements sufficiently to anticipate how architectural decisions impact reliability, performance, and business outcomesSkills and Experience RequiredProficiency building ETL/ELT pipelines in private GCP environmentsExperience with Google Cloud, especially BigQueryExperience designing and implementing data solutions for marketing, advertising, or customer analytics use cases, including integration with Google Marketing Platform products and related marketing vendor APIsStrong Computer Science (CS) fundamentals,



problem solving skills and software engineering skillsA strong ability to understand and organize data from various sourcesStrong expertise in a programming language (preferably Python)Proficiency writing queries with SQLExperience building solutions via API integrationKnowledge of OAuth protocols for API authenticationExperience with quality assurance (QA) and devops processesStrong understanding of security and privacy implications in data pipelinesAbility to identify and resolve performance and data quality issues in data pipelinesStrong critical thinking and problem solving skills with attention to detailExperience mentoring technical colleagues or leading technical discussionsAbility to influence technical decision making, facilitate solution discussions, and build consensus with client and internal stakeholdersExcellent written, verbal, and presentation skills, with the ability to communicate complex technical concepts to both technical and non-technical audiencesAbility to prioritize projects and handle multiple tasks efficientlyA degree in Computer Science, Statistics, Information Systems, or other quantitative fields, or comparable industry experiencePreferred ExperienceExperience with a range of data warehousing and integration platforms and software, such as Snowflake, Databricks and dbtExperience with a wide variety of APIs for marketing platforms and productsExperience with AI deployment in cloud environments, especially GeminiGoogle Cloud Qualified certifications, particularly the Data Engineer, Cloud Database Engineer or ML Engineer certifications, are an asset#J-18808-Ljbffr

📌 Cloud Data Architect (Ottawa)
🏢 Procom
📍 Ottawa