Lead the design and development of data architecture blueprints: Define the technical vision for our data infrastructure, ensuring it meets evolving business needs and supports seamless analytics execution. 

Translate business requirements into technical specifications: Collaborate with stakeholders to understand their data needs and translate them into detailed technical requirements for data pipelines, models, and visualizations. 

Lead the transformation and optimization of our data platform: Partner with the internal data engineering team to modernize and enhance the efficiency and performance of our existing data infrastructure, ensuring it is scalable, reliable, and secure. 

Champion best practices in data management: Establish and enforce coding standards, security protocols, and quality assurance processes to ensure the integrity, reliability, and scalability of our data solutions. 

Enhance and implement data security and privacy measures: Develop and implement robust security and privacy controls to protect sensitive data and comply with relevant regulations. 

Drive innovation with emerging technologies: Stay abreast of cutting-edge data technologies, including cloud platforms (AWS, Azure, Snowflake), data modeling techniques, and machine learning algorithms, to continuously enhance our data capabilities. 

Collaborate with cross-functional teams: Work closely with data scientists, engineers, and business analysts to deliver end-to-end data solutions that drive business value. 

Possesses a BSc in Information Technology, Computer Science, or a related field. 

Has a minimum of 6 years of experience designing, implementing, and maintaining data solutions in complex environments. Proven experience as a Data Architect, with experience leading data engineering teams or projects is preferred. 

Is proficient in data modeling techniques, database architecture, data governance, and programming languages like SQL, Python, Java, Scala. Experience with data engineering frameworks such as EMR/Hadoop, Airflow, and Spark is highly valued. Experience with data modeling in data lakes, including both batch and real-time data pipelines and tools. 

Has a solid understanding of cloud computing platforms (AWS, Azure, Snowflake) and their data services. Experience with professional cloud certifications in data analytics, engineering in AWS, Snowflake, or Azure is highly valued. 

Has experience designing, implementing, and maintaining large and complex data pipelines, including ETL/ELT processes. 

Possesses hands-on experience with business intelligence, analytics, and data visualization tools like Tableau, Power BI, or QlikView. 

Possesses hands-on experience with machine learning algorithms and their application in data-driven solutions. 

Demonstrates excellent communication and interpersonal skills to effectively collaborate with stakeholders, team members, and technical experts.