The Data Architect is responsible for designing, creating, deploying, and managing an organization’s data architecture. This role ensures that data across systems is accurate, accessible, secure, and supports business objectives.
As a Data Architect, you will have extensive experience in development of data intensive systems. This should include working with customers to derive requirements and design solutions to meet their needs. The successful applicant will be expected to have seen a project through from inception to delivery.
To succeed in this position you will need to be proactive, tirelessly collaboratively with IT teams, data engineers, system engineers, and stakeholders to define data models, data flow processes, and governance frameworks.
SKILLS AND KNOWLEDGE REQUIRED
* Bachelor’s degree in STEM, Computer Science, Information Systems, Data Science, or related field (Master’s preferred).
* Strong proficiency in SQL and database technologies (e.g., Oracle, SQL Server, PostgreSQL, MySQL).
* Knowledge of data warehouse and lakehouse architectures
* Familiarity with ETL/ELT and orchestration tools (e.g., Informatica, Talend, Apache Airflow).
* Experience establishing and maintaining data governance frameworks
* Experience complying with data security requirements.
* Excellent problem-solving, communication, and documentation skills.
* Familiarity with AI/ML data pipelines and analytics platforms.
Preferred Qualifications
* Experience with cloud data platforms (e.g., AWS, Azure, Google Cloud).
* Experience with big data technologies (e.g., Hadoop, Spark, Kafka).
* Experience with UML/SYSML.
* Strong understanding of API integration and microservices data flow.
TASKS REQUIRED
* Design and implement enterprise-level data architecture solutions, including databases, data warehouses, and data lakes.
* Develop and maintain logical, physical, and conceptual data models.
* Define data management standards, policies, and best practices.
* Work with data engineers to design and optimize ETL/ELT pipelines for structured and unstructured data.
* Ensure data quality, consistency, and security across platforms.
* Collaborate with business stakeholders to understand data requirements and translate them into technical solutions.
* Evaluate and recommend new data technologies, tools, and platforms to enhance data capabilities.
* Oversee data integration across cloud and on-premises environments.
* Support data governance initiatives, including metadata management, master data management (MDM), and compliance.
* Provide technical leadership and mentorship to data engineering and analytics teams.
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