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Data Architect

  • Toronto, ON, Canada

Contract

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Job details

Job type
Contract
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Experience
10+ years of experience in Data Architecture, Data Engineering, or Enterprise Data Management.
Posting language
English
Posted

Original job description

The Data Architect will be responsible for defining enterprise data strategies, building robust data solutions, and ensuring data quality, governance, security, and accessibility across the organization.

Key Responsibilities

  • Design and implement scalable enterprise data architectures and data management solutions.
  • Develop conceptual, logical, and physical data models to support business and technical requirements.
  • Define data architecture standards, principles, frameworks, and best practices.
  • Architect and optimize data warehouses, data lakes, and modern lakehouse platforms.
  • Design end-to-end data integration, ETL/ELT pipelines, and data transformation solutions.
  • Work with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
  • Implement data governance, data quality, metadata management, and master data management strategies.
  • Ensure data security, privacy, compliance, and access control across enterprise data platforms.
  • Collaborate with business stakeholders, data engineers, data scientists, and application teams.
  • Evaluate emerging data technologies and recommend solutions aligned with business objectives.
  • Optimize data performance, scalability, availability, and cost efficiency.
  • Provide technical leadership and architectural guidance to data engineering teams.

Required Skills & Qualifications

  • 10+ years of experience in Data Architecture, Data Engineering, or Enterprise Data Management.
  • Strong expertise in SQL, relational databases, and NoSQL databases.
  • Hands-on experience with data modeling tools and methodologies.
  • Strong understanding of Data Warehousing, Data Lakes, and Lakehouse architectures.
  • Experience with ETL/ELT tools such as Informatica, Talend, Azure Data Factory, or AWS Glue.
  • Experience with cloud data platforms such as Azure, AWS, or GCP.
  • Knowledge of big data technologies such as Apache Spark, Hadoop, and Kafka.
  • Experience designing batch and real-time data processing architectures.
  • Strong understanding of data governance, data quality, metadata management, and data security.
  • Experience with database technologies such as Oracle, SQL Server, PostgreSQL, Snowflake, or Databricks.
  • Excellent communication, analytical, problem-solving, and stakeholder management skills.

Preferred Qualifications

  • Experience with Snowflake, Azure Databricks, Microsoft Fabric, or AWS Redshift.
  • Knowledge of data mesh, data fabric, and domain-driven data architecture.
  • Experience with CI/CD, Infrastructure as Code, and data DevOps practices.
  • Familiarity with AI/ML data architectures and Generative AI data platforms.
  • Relevant cloud certifications (AWS, Azure, or GCP).
More about this job

Responsibilities

Define enterprise data strategies and design scalable data architectures, models, platforms, and integration pipelines across cloud, warehouse, lake, and lakehouse environments. Establish governance, quality, security, and performance practices while providing architectural leadership and collaborating with business and technical teams.

Requirements

Requires 10 or more years of experience in data architecture, data engineering, or enterprise data management, with strong SQL, database, data modeling, cloud, and ETL/ELT expertise. Candidates should also understand data governance, security, batch and real-time processing, and big data technologies; experience with modern platforms and data DevOps is preferred.

Skills

  • Data Architecture
  • Enterprise Data Strategy
  • Data Modeling
  • Data Warehousing
  • Data Lakes
  • Lakehouse Architecture
  • SQL
  • Relational Databases
  • NoSQL Databases
  • ETL/ELT
  • Cloud Data Platforms
  • Data Governance
  • Data Quality
  • Data Security
  • Apache Spark
  • Kafka

Visa sponsorship

Not detected in the job text

Categories

  • Data & Analytics
  • Technology
  • Software
  • Management & Leadership

Keywords

  • Enterprise Data Architecture
  • Data Management
  • SQL
  • Relational Databases
  • NoSQL Databases
  • Data Modeling
  • Data Warehousing
  • Data Lakes
  • Lakehouse
  • ETL/ELT
  • Informatica
  • Talend
  • Azure Data Factory
  • AWS Glue
  • AWS
  • Azure
  • Google Cloud Platform
  • Apache Spark
  • Hadoop
  • Kafka
  • Data Governance
  • Data Quality
  • Metadata Management
  • Master Data Management
  • Oracle
  • SQL Server
  • PostgreSQL
  • Snowflake
  • Databricks
  • Data Mesh

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