Data Architect

1 month ago

Old Toronto, Ontario, Canada Project Limited Full time
Role Summary

As a Data Architect at Project X Ltd., you will be responsible for designing, implementing, and overseeing end-to-end solutions that address designing scalable and efficient data solutions, and complex business challenges and unlock the value of data for our clients.

Key Responsibilities
  1. Data Strategy and Architecture:
    • Define and execute data strategies that align with clients' business objectives and support their digital transformation initiatives.
    • Lead the development of enterprise-wide data architectures, including conceptual, logical, and physical data models, data flows, and integration patterns.
  2. Data Governance and Compliance:
    • Establish and enforce data governance policies, standards, and best practices to ensure data quality, integrity, and security.
    • Ensure compliance with regulatory requirements such as GDPR, CCPA, HIPAA, and industry-specific standards.
  3. Data Integration and Migration:
    • Lead the design and implementation of data integration solutions to consolidate, transform, and migrate data from disparate sources.
    • Architect data pipelines and orchestration workflows using modern integration technologies and platforms.
  4. Advanced Analytics and Machine Learning:
    • Collaborate with data scientists and analytics teams to design and implement advanced analytics solutions, including predictive modeling and machine learning algorithms.
    • Architect data lakes and analytical environments to support exploratory data analysis and data science initiatives.
  5. Cloud Data Platform and Big Data Solutions:
    • Design and implement scalable and cost-effective data architectures on cloud platforms such as AWS, Azure, or Google Cloud Platform.
    • Architect big data solutions leveraging technologies such as Hadoop, Spark, Kafka, and NoSQL databases.
  6. Data Visualization and Insights Delivery:
    • Develop interactive dashboards, reports, and visualizations to deliver actionable insights and key performance indicators (KPIs) to stakeholders.
    • Utilize data visualization tools such as Power BI, Tableau, or Looker to create compelling and intuitive visualizations.
  7. Client Engagement and Thought Leadership:
    • Serve as a trusted advisor to clients, providing strategic guidance, technical expertise, and thought leadership on data architecture and analytics topics.
    • Lead client workshops, training sessions, and presentations to evangelize data-driven decision-making and promote best practices.
Requirements
  • College, Bachelor's, or Master's degree in Computer Science, Information Systems, or a related field.
  • Deep understanding of cloud computing principles and experience with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud Platform).
  • 5+ years of experience in data architecture, data engineering, and analytics, with a focus on enterprise-scale solutions.
  • Proven track record of designing and implementing complex data architectures and solutions across multiple industries and domains.
  • Expertise in data modeling, database design, and optimization techniques, with hands-on experience in relational and NoSQL databases.
  • Strong programming skills in languages such as SQL, Python, or Scala, with experience in data manipulation, transformation, and analysis.
  • Excellent communication, presentation, and stakeholder management skills, with the ability to effectively communicate technical concepts to non-technical audiences.
  • Strong leadership and team management skills, with the ability to mentor junior team members and lead cross-functional project teams.
Nice to Have
  • Certification in relevant technologies or methodologies (e.g., AWS Certified Solutions Architect, Microsoft Certified: Azure Solutions Architect Expert, Certified Data Management Professional).
  • Experience with data governance frameworks, metadata management tools, and data catalog solutions.
  • Knowledge of emerging trends and technologies in data architecture, such as data mesh, event-driven architectures, and streaming analytics.

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