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GCP Data Engineer

1 month ago

Lake City, United States Tata Consultancy Services Full time

Job Location: Atlanta GA/Edison NJ / Dallas TX / Duluth GA Technical Skills: At least 8 years of overall experience in building ETL/ELT, data warehousing and big data solutions. At least 5 years of experience in building data models and data pipelines to process different types of large datasets. Proven expertise in relational and dimensional data modeling. Understand PII standards, processes, and security protocols. Experience in building data warehouse using Cloud Technologies such as AWS or GCP Services, and Cloud Data Warehouse preferably Google BigQuery. In depth knowledge in Big Data solutions Strong SQL knowledge – able to translate complex scenarios into queries. Strong Programming experience in Java or Python Experience in Google Cloud platform (especially BigQuery & Dataflow) Experience with Google Cloud SDK & API Scripting Experience in Onsite-Offshore coordination Experience in Test Driven Development Experience in Agile processes and DevOps methodologies. Experience with Data modeling and mapping. Google Cloud Professional Data Engineer Certification is an advantage. Programming Language – Java / Python Google Cloud – Big Query, Pub/ Sub, Dataflow, Composer DAGs, Cloud storage CI/CD – GitHub, Jenkins Experience in NoSQL Databases is an added advantage. Experience of Retail domain will be an added advantage. Roles & Responsibility: Drives world-class design and development of analytical data pipelines. Provides thought leadership and propose industry standards and implementations. Adhere to processes to ensure data pulled from various sources meets quality standards, is curated and enhanced for analytical use and there is a "single source of truth" Maintain database structure and standard definitions for business users across Macy's Work with data architects to build the foundational extract / load / transform process and regularly review the architecture and recommend effectiveness improvements. Collaborate with Technology to future-proof data & analytics software, tools, and code to reduce risk and support pipeline owners Work with Legal and Privacy teams to adhere to data privacy and security standards Work with Data Architect to implement the data models, standards, and quality rules Work with the Data Science team to understand data formatting and sourcing needs to enable them to build out use cases as efficiently as possible. Keep data separated and secured using masking and encryption. Explain the requirement to offshore team and create Interface to determine the most efficient and cost-effective approach to meet business requirements. Daily onsite-offshore coordination

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