Senior Cloud Data Solutions Architect

Há 23 horas

Curitiba, Brasil Bebeedata Tempo inteiro

Job DescriptionAs a senior cloud data engineer, you will lead the design, architecture, and implementation of secure, scalable data solutions on AWS.You will collaborate closely with cross-functional teams to translate business requirements into robust data pipelines and products.The responsibilities include leading the design, development, and maintenance of highly scalable, secure, and resilient data pipelines and systems on cloud platforms.You will also architect and implement advanced data integration solutions to support complex analytics, business intelligence, and enterprise reporting needs.Furthermore, you will ensure the highest standards of data quality, integrity, and security through comprehensive testing, validation, and robust governance practices.Additionally, you will monitor, optimize, and scale data workflows to achieve performance, reliability, and cost-efficiency targets across both cloud and legacy environments.Moreover, you will proactively identify, investigate, and resolve data-related issues, providing technical leadership, mentorship, and guidance to junior team members.Finally, you will champion continuous improvement by staying current with industry trends, emerging technologies, best practices, and driving innovation in data engineering processes and solutions.Required Skills and QualificationsMinimum of 7 years of progressive experience in data engineering, with a strong emphasis on designing and implementing cloud-based solutions.Advanced proficiency in SQL, with hands-on experience in both relational (e.g., Oracle, SQL Server, MySQL, Snowflake) and NoSQL (e.g., MongoDB, DynamoDB) databases.Extensive experience architecting and operating data platforms on AWS and Azure; relevant cloud certifications (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate) strongly preferred.Deep knowledge of data warehousing concepts, ETL/ELT processes, data modeling, and enterprise data governance frameworks.Demonstrated success in leading and mentoring data engineering teams, driving technical excellence and fostering collaborative environments.Exceptional problem-solving skills, attention to detail, and the ability to work independently and proactively in fast-paced settings.Advanced proficiency in Python and Bash for automation, orchestration, and data processing tasks within AWS environments.Outstanding communication, leadership, and cross-functional collaboration abilities, with a proven track record of partnering with business and technical stakeholders.Expertise with Snowflake, dbt, GitHub, Control-M, and familiarity with modern data engineering frameworks (e.g., Airflow, Fivetran, Matillion) as deployed on AWS.Solid understanding of both traditional on-premises (virtual/physical) and AWS cloud-based infrastructure, including Windows and Linux environments.BenefitsYou should have a minimum of 7 years of experience in data engineering with a focus on cloud-based solutions, and be proficient in SQL, AWS, and Azure.Additionally, you should have expertise in Snowflake, dbt, and modern data engineering frameworks, as well as experience in leading and mentoring data engineering teams.Skills required: Cloud Data Engineering, Big Data Architecture, SQL, AWS, Azure, Snowflake, dbt, Python, Bash.

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