Data Architect

Key Responsibilities:

Lead the design and implementation of data architecture solutions for large-scale data migration projects from on-premises environments to AWS Cloud.
Develop comprehensive architecture artifacts, including high-level designs, data flow diagrams, and technical documentation, to support complex data warehousing and analytics initiatives.
Architect and implement multi-layer Lakehouse solutions, ensuring efficient data storage, processing, and analytics capabilities.
Design and build large-scale data warehouses and data marts using tools like Netezza, Snowflake, and Talend, ensuring data quality, integrity, and performance.
Collaborate with stakeholders to gather and define data requirements, ensuring alignment with business objectives and technical feasibility.
Lead the development of data mapping and transformation processes to support seamless data migration and integration.
Utilize AWS Cloud services, including Lambda and other serverless technologies, to build scalable and cost-effective data solutions.
Provide technical leadership and guidance to data engineering and development teams, ensuring adherence to best practices in data architecture and engineering.
Monitor and optimize data architectures for performance, scalability, and cost-efficiency, addressing any bottlenecks or issues proactively.
Stay current with emerging trends and technologies in data architecture, data warehousing, and cloud computing, recommending new tools and approaches as needed.

Qualifications:

10+ years of experience as a Data Architect, with a strong focus on data warehousing, data migration, and cloud-based solutions.
Extensive experience designing and implementing large-scale data warehouses and data marts.
Proven expertise in data architecture and solution design for complex data migration projects, particularly from on-premises to cloud environments.
Proficiency with data warehousing tools such as Netezza, Snowflake, and ETL tools like Talend.
Strong knowledge of AWS Cloud architecture and services, including Lambda and other serverless computing technologies.
Deep understanding of multi-layer Lakehouse architectures and best practices in data storage and analytics.
Strong SQL and Python skills, with the ability to write and optimize complex queries and scripts.
Excellent communication and collaboration skills, with the ability to work effectively with both technical and business teams