AWS Data Architect

Job description

AWS Data Architect Role: T0 **The Ideal Professional For This AWS Architect Role Will** - Have a passion for design, technology, analysis, collaboration, agility, and planning, along with a drive for continuous improvement and innovation. - Exhibit expertise in managing high-volume data projects that leverage Cloud Platforms, Data Warehouse reporting and BI Tools, and the development of relational databases. - Research, identify, and internally market enabling data management technologies based on business and end-user requirements. - Seek ways to apply new technology to business processes with a focus on modernizing the approach to data management. - Consult with technical subject matter experts and develop alternative technical solutions. Advise on options, risks, costs versus benefits, and impact on other business processes and system priorities. - Demonstrate strong technical leadership skills and the ability to mentor others in related technologies. **Qualifications** - Bachelor's degree in a computer-related field or equivalent professional experience is required. - Preferred master’s degree in computer science, information systems or related discipline, or equivalent and extensive related project experience. - 10+ years of hands-on software development experience building data platforms with tools and technologies such as Hadoop, Cloudera, Spark, Kafka, Relational SQL, NoSQL databases, and data pipeline/workflow management tools. - 6+ years of experience working with various AWS cloud platforms. - Experience in AWS data platform migration and hands-on experience working with AWS and its tools - Experience in Data & Analytics projects is a must. - Data modeling experience – relational and dimensional with consumption requirements (reporting, dashboarding, and analytics). - Thorough understanding and application of AWS services related to Cloud data platform and Datalake implementation – S3 Datalake, AWS EMR, AWS Glue, Amazon Redshift, AWS Lambda, and Step functions with file formats such as Parquet, Avro, and Iceberg. - Must know the key tenets of architecting and designing solutions on AWS Clouds. - Expertise and implementation experience in data-specific areas, such as AWS Data Lake, Data Lakehouse Architecture, and SQL Datawarehouse. - Apply technical knowledge to architect and design solutions that meet business and IT needs, create Data & Analytics roadmaps, drive POCs and MVPs, and ensure the long-term technical viability of new deployments, infusing key Data & Analytics technologies where applicable. - Be the Voice of the Customer to share insights and best practices, connect with the Engineering team to remove key blockers, and drive migration solutions and implementations. - Familiarity with tools like DBT, Airflow, and data test automation. - MUST have experience with Python/PySpark/Scala in Big Data environments. - Strong skills in SQL queries in Big Data tools such as Hive, Impala, Presto. - Experience working with and extracting value from large, disconnected, and/or unstructured datasets.