Data Architect

Position Overview:

As a Data Architect, you are responsible for designing and managing scalable, secure, and high-performance data architectures that support GEDU and customer needs. This role ensures that the GEDU’s data assets are structured and managed in a way that enables the business to generate insights, make data-driven decisions, and maintain data integrity across the GEDU and Customers. The Data Architect will work closely with business leaders, data engineers, data scientists, and IT teams to align the data architecture with the GEDU’s strategic goals.

Key Responsibilities:

Data Architecture Design:

• Design, develop, and maintain the enterprise data architecture, including data models, database schemas, and data flow diagrams.
• Develop a data strategy and roadmap that aligns with GEDU business objectives and ensures the scalability of data systems.
• Architect both transactional (OLTP) and analytical (OLAP) databases, ensuring optimal performance and data consistency.

Data Integration & Management:

• Oversee the integration of disparate data sources into a unified data platform, leveraging ETL/ELT processes and data integration tools.
• Design and implement data warehousing solutions, data lakes, and/or data marts that enable efficient storage and retrieval of large datasets.
• Ensure proper data governance, including the definition of data ownership, security, and privacy controls in accordance with compliance standards (GDPR, HIPAA, etc.).

Collaboration with Stakeholders:

• Work closely with business stakeholders, including analysts, developers, and executives, to understand data requirements and ensure that the architecture supports analytics and reporting needs.
• Collaborate with DevOps and engineering teams to optimize database performance and support large-scale data processing pipelines.

Technology Leadership:

• Guide the selection of data technologies, including databases (SQL/NoSQL), data processing frameworks (Hadoop, Spark), cloud platforms (Azure is a must), and analytics tools.
• Stay updated on emerging data management technologies, trends, and best practices, and assess their potential application within the organization.

Data Quality & Security:

• Define data quality standards and implement processes to ensure the accuracy, completeness, and consistency of data across all systems.
• Establish protocols for data security, encryption, and backup/recovery to protect data assets and ensure business continuity.

Mentorship & Leadership:

• Lead and mentor data engineers, data modelers, and other technical staff in best practices for data architecture and management.
• Provide strategic guidance on data-related projects and initiatives, ensuring that all efforts are aligned with the enterprise data strategy.

Extensive Data Architecture Expertise:

• Over 7 years of experience in data architecture, data modeling, and database management.
• Proficiency in designing and implementing relational (SQL) and non-relational (NoSQL) database solutions.
• Strong experience with data integration tools (Azure Tools are a must + any other third-party tools), ETL/ELT processes, and data pipelines.

Advanced Knowledge of Data Platforms:

• Expertise in Azure cloud data platform is a must. Other platforms such as AWS (Redshift, S3), Azure (Data Lake, Synapse), and/or Google Cloud Platform (BigQuery, Dataproc) is a bonus.
• Experience with big data technologies (Hadoop, Spark) and distributed systems for large-scale data processing.
• Hands-on experience with data warehousing solutions and BI tools (e.g., Power BI, Tableau, Looker).

Data Governance & Compliance:

• Strong understanding of data governance principles, data lineage, and data stewardship.
• Knowledge of industry standards and compliance requirements (e.g., GDPR, HIPAA, SOX) and the ability to architect solutions that meet these standards.

Technical Leadership:

• Proven ability to lead data-driven projects, manage stakeholders, and drive data strategies across the enterprise.
• Strong programming skills in languages such as Python, SQL, R, or Scala.

Pre-Sales Responsibilities:

• Stakeholder Engagement:

  Work with product stakeholders to analyze functional and non-functional requirements, ensuring alignment with business objectives.

• Solution Development:

  Develop end-to-end solutions involving multiple products, ensuring security and performance benchmarks are established, achieved, and maintained.

• Proof of Concepts (POCs):

  Develop POCs to demonstrate the feasibility and benefits of proposed solutions.

• Client Communication:

  Communicate system requirements and solution architecture to clients and stakeholders, providing technical assistance and guidance throughout the pre-sales process.

• Technical Presentations:

  Prepare and deliver technical presentations to prospective clients, demonstrating how proposed solutions meet their needs and requirements.

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