Data Engineer
1 dia atrás
Come to one of the biggest IT Services companies in the world Here you can transform your career Why to join TCS? Here at TCS we believe that people make the difference, that's why we live a culture of unlimited learning full of opportunities for improvement and mutual development. The ideal scenario to expand ideas through the right tools, contributing to our success in a collaborative environment. We are looking for Data Engineer who wants to learn and transform his career. In this role you will: Extensive experience (5+ years) working as a Data Engineer, with a strong focus on AWS technologies and serverless architectures; Experience working as a Data Engineer, with focus on Azure is valuable; In-depth knowledge of AWS services such as S3, Lambda, Glue, Athena, Redshift, and DynamoDB, and their capabilities for building scalable data processing systems; Proven expertise in designing and implementing AWS serverless architectures for large-scale data processing and storage; Strong programming skills in languages like Python, Java, or Scala, along with experience using SQL for data manipulation and querying; Hands-on experience with data integration and ETL tools, such as AWS Glue or Apache Spark, for transforming and processing data; English And much better if you stand out for: Familiarity with data modeling techniques and data warehousing concepts, including star and snowflake schemas; Solid understanding of data security, access control, and compliance requirements in a data-driven environment; Experience with data visualization tools (e.g., Tableau, Power BI) and the ability to collaborate with analysts and data scientists to deliver actionable insights; Strong problem-solving and analytical skills, with a detail-oriented approach to ensure data accuracy and integrity; Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment Key Responsibilities: Design and implement an AWS Serverless DataLake architecture to efficiently handle large volumes of data and support various data processing workflows; Develop data ingestion pipelines and data integration processes, ensuring the smooth and reliable
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