Technical Architect - Data Engineer

Key Responsibilities:

1. Data Architecture:

• Define and maintain the overall data architecture, including data models, data flow, and data storage.

• Collaborate with stakeholders to understand business requirements and translate them into data architecture solutions.

• Ensure data solutions are scalable, efficient, and aligned with the organization's objectives.

2. Technical Leadership:

• Provide technical leadership and guidance to the data engineering team.

• Mentor and coach team members, fostering their professional growth.

• Lead and facilitate technical discussions, architecture reviews, and decision-making processes.

3. Data Engineering:

• Design and develop data pipelines, ETL processes, and data integration solutions.

• Implement data transformation and data enrichment strategies.

• Optimize data workflows for performance, reliability, and scalability.

4. Data Modeling:

• Develop and maintain data models, data dictionaries, and schema designs.

• Ensure data models support business requirements, reporting, and analytics needs.

• Implement best practices for data modeling and database design.

5. Data Governance and Security:

• Implement data governance processes to ensure data quality, consistency, and compliance.

• Collaborate with security teams to establish and enforce data security and privacy policies.

• Monitor and audit data access and usage to protect sensitive information.

6. Integration and API Design:

• Design and implement data integrations with external systems and APIs.

• Develop RESTful APIs for data access and consumption.

• Ensure data interoperability and data exchange standards are met.

7. Documentation and Best Practices:

• Create and maintain comprehensive technical documentation, including data architecture diagrams and design documents.

• Establish and enforce data engineering best practices and coding standards.

• Promote knowledge sharing and cross-training within the team.

8. Vendor and Stakeholder Collaboration:

• Collaborate with data tool vendors and external partners to leverage their expertise and resources.

• Build and maintain strong relationships with stakeholders to ensure alignment with data initiatives.