AWS Data Architect- Leadership

Role Overview: You will be the Technical Leader for the AWS Data Engineering practice, responsible for driving the Data Engineering strategy, architecting scalable data solutions, and leading data projects on AWS. Your deep understanding of AWS services and data engineering best practices will be crucial for the success of the practice. This role offers the opportunity to establish and enhance the company's Data Engineering Services Practice, collaborating closely with senior stakeholders to deliver technical solutions in a dynamic and fast-paced environment. Key Responsibilities: - Act as a visionary leader in data engagements, steering, motivating, and driving exceptional performance. - Conduct proof-of-concept projects to recommend scalable data solutions with high ROI. - Make informed architectural decisions prioritizing customer needs. - Guide and mentor engineers, ensuring high standards of code quality through code reviews. - Collaborate with sales, pre-sales, and solution teams to develop proposals aligning with company objectives. - Design and implement data lakes, cloud data warehouses, data models, and data quality assessments. - Lead the development and management of data infrastructure, ensuring automation and data integrity. - Design scalable data solutions using AWS services, aligning with business requirements and best practices. - Oversee data engineering projects from inception to completion, ensuring data quality and security. - Stay updated on data engineering and AWS technologies, driving continuous improvement initiatives. - Experiment with new tools and technologies to enhance data processing efficiency. Qualifications Required: - Bachelor's or Master's degree in Engineering or Technology. - 15+ years of hands-on experience in Data space. - Experience with large-scale data projects and projects across multiple geographic regions. - Proficiency in AWS data services such as Glue, Redshift, S3, Athena, EMR, Lambda, and RDS. - Strong understanding of AWS architecture and best practices for data engineering. - Proficiency in SQL and Python for data processing. - Experience with data warehousing concepts, ETL/ELT processes, and data integration. - Familiarity with data serialization formats and optimizing data pipelines. - Hands-on experience with big data processing frameworks like Apache Spark, Hadoop, and Kafka. - Knowledge of data governance frameworks, data lifecycle management, and data retention policies. - Ability to implement and manage data quality frameworks. - Experience with data visualization tools such as PowerBI or Tableau. Company details: Omit this section as no additional details of the company are provided in the job description. Role Overview: You will be the Technical Leader for the AWS Data Engineering practice, responsible for driving the Data Engineering strategy, architecting scalable data solutions, and leading data projects on AWS. Your deep understanding of AWS services and data engineering best practices will be crucial for the success of the practice. This role offers the opportunity to establish and enhance the company's Data Engineering Services Practice, collaborating closely with senior stakeholders to deliver technical solutions in a dynamic and fast-paced environment. Key Responsibilities: - Act as a visionary leader in data engagements, steering, motivating, and driving exceptional performance. - Conduct proof-of-concept projects to recommend scalable data solutions with high ROI. - Make informed architectural decisions prioritizing customer needs. - Guide and mentor engineers, ensuring high standards of code quality through code reviews. - Collaborate with sales, pre-sales, and solution teams to develop proposals aligning with company objectives. - Design and implement data lakes, cloud data warehouses, data models, and data quality assessments. - Lead the development and management of data infrastructure, ensuring automation and data integrity. - Design scalable data solutions using AWS services, aligning with business requirements and best practices. - Oversee data engineering projects from inception to completion, ensuring data quality and security. - Stay updated on data engineering and AWS technologies, driving continuous improvement initiatives. - Experiment with new tools and technologies to enhance data processing efficiency. Qualifications Required: - Bachelor's or Master's degree in Engineering or Technology. - 15+ years of hands-on experience in Data space. - Experience with large-scale data projects and projects across multiple geographic regions. - Proficiency in AWS data services such as Glue, Redshift, S3, Athena, EMR, Lambda, and RDS. - Strong understanding of AWS architecture and best practices for data engineering. - Proficiency in SQL and Python for data processing. - Experience with data warehousing concepts, ETL/ELT processes, and data integration. - Familiarity with data serialization formats and optimizing data pipelines. -