Enterprise Data Architect

2 days ago


Markham Ontario IP, CA LTIMindtree Full time

Title: Enterprise Data Architect

Location: Markham, ON (Hybrid)

Contract


Key Responsibilities:


Enterprise Architecture & Data Strategy:

  • Lead the creation and execution of data architecture strategies aligned with business goals and requirements.
  • Collaborate with stakeholders across the organization to understand data needs and develop end-to-end solutions.
  • Ensure scalable, secure, and sustainable data architecture while optimizing data flow and storage strategies.

Data Platform & Lifecycle Management:

  • Design, implement, and manage enterprise data platforms with a focus on modern data practices and cloud computing.
  • Oversee the data lifecycle management processes, ensuring data quality, retention, security, and governance.
  • Guide the adoption of the medallion architecture pattern for structured and organized data pipelines.

Data Product Management:

  • Champion the concept of Data as a Product, ensuring that data products are well-defined, maintainable, and provide value to the business.
  • Facilitate the transformation of raw data into actionable insights and ready-to-use products for data consumers.

Cloud & Modern Development Practices:

  • Leverage cloud technologies to build scalable and high-performance data solutions.
  • Drive best practices in modern development methodologies, including CI/CD and Agile practices, to enhance data product delivery.

Legacy to Modern Platform Migration:

  • Lead the efforts to convert legacy systems and data policies to modern data platforms while minimizing disruption to existing business processes.
  • Oversee data migration strategies to ensure seamless transitions and the integration of legacy systems with cloud-based architectures.

Data Science & MLOps:

  • Collaborate with data science teams to support the development, deployment, and operationalization of machine learning models.
  • Provide guidance on Data Science Machine Learning (DSML) platforms and MLOps practices to streamline model development and lifecycle management.


Required Skills and Qualifications:

  • Proven experience in Enterprise Architecture with a focus on data platforms, data governance, and cloud technologies.
  • Strong expertise in data lifecycle management, including data modeling, data retention, and data governance principles.
  • Solid understanding of the Medallion Architecture pattern and its application in large-scale data systems.
  • In-depth knowledge of Data as a Product concepts and ability to translate business requirements into tangible data solutions.
  • Expertise in modern cloud platforms (AWS, Azure, GCP) and cloud-native development practices.
  • Extensive experience with data science platforms, machine learning operations (MLOps), and facilitating the integration of data science models into production environments.
  • Proficient in designing solutions that convert legacy data systems to modern data architectures.
  • Strong communication and leadership skills to work effectively with cross-functional teams and business leaders.
  • Experience with data integration, ETL processes, and data warehousing concepts.


Preferred Qualifications:

  • Certification in cloud platforms (AWS Certified Solutions Architect, Azure Architect, etc.)
  • Experience with modern data engineering tools and platforms such as Apache Kafka, Spark, or Databricks.
  • Familiarity with data privacy and compliance frameworks such as GDPR, CCPA, and HIPAA.


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