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Data Engineer at Capgemini. Capgemini is looking for a skilled Data Engineer to join our dynamic team.. In this role, you will be responsible for designing, implementing, and maintaining data pipelines and architectures, ensuring efficient data processing and storage. You will collaborate closely with data scientists and analysts to support data analysis and reporting needs, making sure data quality and integrity are upheld throughout the data lifecycle. Your role will be pivotal in driving data initiatives and optimizing data workflows, enabling better decision-making through data-driven insights.. As part of a leading global consulting firm, Capgemini provides opportunities to work on diverse projects and leverage cutting-edge technologies in the data engineering space.. Role Description:. . Consults independently, works iteratively, and is viewed as an expert on data projects of a complex nature.. . Ability to understand design requirement and existing business processes to lead in the design, development, and implementation of data products in partnership with business partners and data scientists.. . Produces complex data building blocks, data models, and data flows working with business partners and data scientists within personal lines and distribution domains to deliver requests such as dimensional data models, standard and ad hoc reporting, data feeds, dashboard reporting, ad hoc analysis, data profiling etc.. . Designs and manages highly complex projects while handling multiple complex cross-functional projects.. . Preps/cleanses data to optimize for downstream reporting using Farmers standards.. . Functions as an expert in serving as a SME for appropriate data sources and for how best to operationalize solutions working closely with business partners and data scientists.. . Acts as a conduit between business and IT teams for all aspects of the work.. . Create Dimensional Data Models, STTM’s and other technical documents for offshore developers and oversee technical delivery of projects by conducting code reviews, documentation reviews etc.. . Design, develop and maintain scalable and efficient data pipelines using cloud services such as AWS Glue, Lambda, Airflow, Event Bridge or equivalent/ related. Performs other duties as assigned.. . Total Work Experience: . Minimum Required: 4-6 years . English Proficiency: . Intermediate. Required Education: . Bachelor's Degree in Computer Science, Information Technology, or related field. . Additional Preferred Branch(es) of Study. • . Practical knowledge of SQL, Dimensional modeling, Query tuning, ETL orchestration, PowerBI, Python, preferred. . • Hands-on experience with multiple cloud platforms including AWS, Google, and Azure preferred with exposure to services like S3, IAM roles, EC2 or equivalent. • Hand on experience with developing on SSIS and SSAS, preferred. . • Hands-on experience of SQL, Query tuning, AWS Glue, Python, PySpark preferred. . • Hands-on experience with multiple cloud platforms including AWS, and Azure. . • Hands-on experience with RESTful APIs and methods, status codes, request response cycles. • Hands-on experience with data serialization formats and proficiency in working with data formats such as JSON, PARQUET, XML . • Hands-on experience in CI/CD framework to enable automated deployments.. • Solid ability to consume APIS from various sources, integrate into code, extract relevant data and handle different response formats.. • Understanding of API security best practices, including authentication, authorization and data encryption. • Ability to understand API documentation (e.g. Swagger, OpenApi).. • Knowledge of data quality and data governance processes . • Possesses strong technical aptitude, preferred. . • Strong verbal communication and listening skills, preferred. . • Extensive experience interacting with senior leadership stakeholders around the topics of data access, quality, appropriate use, metric definitions and standardization, preferred. . • Effectively coaches junior members and delivers constructive feedback. . Company Location: Mexico.