Enterprise Data Architect

The Enterprise Data Architect will be responsible for designing, creating, deploying, and managing the organization’s data architecture. This role involves defining how the data will be stored, consumed, integrated, and managed by different data entities and IT systems, as well as any applications using or processing that data. The Enterprise Data Architect will work closely with IT and business leaders to develop a data strategy that meets the needs of the organization.

Key Responsibilities :

Data Strategy Development:

1. Develop and implement an enterprise data strategy that aligns with the organization’s goals and objectives.
2. Define data architecture standards, principles, and best practices.

Data Architecture Design:

1. Design and implement effective database solutions and models to store and retrieve company data.
2. Create and maintain data models, data flow diagrams, and data dictionaries.

Data Integration:

1. Ensure data integration across various systems and platforms.
2. Develop and maintain ETL (Extract, Transform, Load) processes.

Data Governance:

1. Establish and enforce data governance policies and procedures.
2. Ensure data quality, data security, and data privacy compliance.

Collaboration and Communication:

1. Collaborate with IT and business teams to understand data requirements and translate them into technical solutions.
2. Communicate data architecture strategies and solutions to stakeholders.

Technology Evaluation and Implementation:

1. Evaluate and recommend new data technologies and tools.
2. Lead the implementation of new data management technologies.

Performance Monitoring and Optimization:

1. Monitor and optimize data systems for performance and scalability.
2. Troubleshoot and resolve data-related issues.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• Proven experience as a Data Architect, Data Scientist, or similar role.
• 10+ years experience in a similar role.
• In-depth understanding of database structure principles.
• Experience with data modeling tools and techniques.
• Knowledge of data governance and data quality management.
• Familiarity with data warehousing, data lakes, and big data technologies.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.

Preferred Skills:

• Experience designing enterprise integrations.
• Experience with cloud Infrastructure platforms (e.g., AWS, Azure, Google Cloud).
• Experience with Software as a Service platform integration and management.
• Proficiency in SQL and other database query languages.
• Proficiency in Python, R or other data analysis or general purpose programming language.
• Knowledge of data visualization tools (e.g., Tableau, Power BI).
• Understanding of machine learning and AI concepts.
• Strong Linux Skills.
• Strong Mulesoft Skills.
• Salesforce and Heroku experience.
• DevSecOps experience.

Work Environment:

• This position may require occasional travel.
• The role involves working with global teams across different time zones.

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