Mid/Senior Data Architect

Main Responsibilities:

• Design and implement the organization's overall data architecture, including data models, database systems, data pipelines, and data warehousing solutions.
• Collaborate with stakeholders across the business and IT to understand data requirements and translate them into robust and scalable data solutions.
• Develop and maintain data standards, policies, and procedures to ensure data quality, integrity, security, and compliance.
• Evaluate and recommend new data technologies and tools to optimize data management and analytics capabilities.
• Lead and mentor data engineers and other technical team members on data architecture best practices.
• Design and implement data integration and ETL/ELT processes to move and transform data across various systems.
• Ensure the scalability, performance, and reliability of data systems.
• Stay up-to-date with the latest trends and advancements in data architecture and related technologies.
• Participate in the development and execution of the data strategy roadmap.
• Troubleshoot and resolve data-related issues and provide technical support.

Required Qualifications:

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• 7-10 years of experience in data modeling, database design, and data warehousing.
• Proven experience designing and implementing data architectures for complex systems.
• Strong understanding of different database technologies (e.g., relational, NoSQL, cloud-based).
• Experience with data integration and ETL/ELT tools and techniques.
• Proficiency in data modeling tools and methodologies.
• Solid understanding of data governance, data quality, and data security principles.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.

Preferred:

• Experience with big data technologies (e.g., Hadoop, Spark).
• Familiarity with data science and machine learning concepts.
• Relevant certifications (e.g., AWS Certified Data Analytics – Specialty, Google Cloud Professional Data Engineer).
• Experience in the Telecom or Banking domain.
• Experience with data visualization tools.
• Experience leading technical teams.