at Capgemini America, Inc. in Chicago, Illinois, United States
Job Description
Capgemini America, Inc. (Sogeti division) seeks IT professionals to fill multiple positions in Chicago, IL and various unanticipated sites throughout the U.S. Entry through Sr. level positions available.
Duties: Apply strong understanding of data architecture principles and guidelines including data modeling, data integration, and data storage concepts to develop scalable and robust solution that provide insights to the business. Design and build advanced data lake, data warehouse and data marts enabling data governance, monitoring data quality, and utilizing a high-performance data lifecycle management framework to ensure data integrity and reliability. Analyze data storage and processing requirements to choose the right technology across various options such as relational databases, data warehouses, NoSQL databases, and big data technologies like Hadoop and Spark. Ensure the alignment of data solutions with the client’s strategic goals. Bridge the gap between technical expertise and business needs, working closely with stakeholders to craft data-driven solutions that drive operational efficiency and innovation. Mentor technical leads and junior data architect. Guide and support the technical team, provide guidance on the solution/design and technical challenges. Collaborate closely with cross-functional teams and stakeholders to architect and design cutting-edge data solutions that address complex business challenges. Implementation of data strategies, conduct proof of concepts, ensuring optimal performance, scalability, and data integrity. Assess project outcomes, identify areas for enhancement, and implement best practices. Proactively seek opportunities to optimize processes, workflows, and technical solutions. Provide technical sales support, collaborate with the sales team to deeply understand client requirements, challenges, and business objectives. Design the solution that Fit to purpose. Develop and deliver impactful technical presentations and demonstrations. Provide guidance on technical queries, engage in discussions, and support post-sales transition. Tool evaluation initiatives, ensuring the selection of optimal technologies for data solutions. Deep understanding of data architecture and technical expertise to assess, recommend, and implement the most suitable tools for projects. Analyze tools capabilities, features, scalability, performance, and compatibility with existing systems. Stay informed about industry advancements, integrating relevant innovations into project approaches. Introduce new technologies and thought leadership to the customer to solve business challenges. Utilize experience with Languages: SQL, Python, Linux/UNIX shell scripting; Databases: MS SQL Server, Oracle; Big Data Technology: Apache Spark, Data Lakehouse, Data Warehousing, Data Mining, Predictive analytics; ETL Tools: Azure Data Factory, Glue; Data Analytic Tools: Tableau, PowerBI, Google Analytics, Looker; Cloud: Microsoft Azure, Databricks, AWS, GCP (Google Cloud Platform); Project Management: Agile Scrum, Jira; Version Control Tools: Github, Azure Devops.
