AWS Data Engineer With Data Modelling Cognizant

About Cognizant

Cognizant is a multinational information technology services and consulting firm headquartered in the United States. Its headquarters are located in Teaneck, New Jersey, in the United States. Cognizant is listed on the NASDAQ-100 under the symbol CTSH.

Job Description

Job Summary Experience : 5 - 8 Years Location : Bangalore Contribute to building state-of-the-art data platforms in AWS, leveraging Python and Spark. Be part of a dynamic team, building data solutions in a supportive and hybrid work environment. This role is ideal for an experienced data engineer looking to step into a leadership position while remaining hands-on with cutting-edge technologies. You will design, implement, and optimize ETL workflows using Python and Spark, contributing to our robust data Lakehouse architecture on AWS. Success in this role requires technical expertise, strong problem-solving skills, and the ability to collaborate effectively within an agile team. Must Have Tech Skills Demonstrable experience as a senior data engineer. Expert in Python and Spark, with a deep focus on ETL data processing and data engineering practices. Experience of implementing data pipelines using tools like EMR, AWS Glue, AWS Lambda, AWS Step Functions, API Gateway, Athena Experience with data services in Lakehouse architecture. Good background and proven experience of data modelling for data platforms Nice To Have Tech Skills A masters degree or relevant certifications (e.g., AWS Certified Solutions Architect, Certified Data Analytics) is advantageous Key Accountabilities Provides guidance on best practices in design, development, and implementation, ensuring solutions meet business requirements and technical standards. Works closely with architects, Product Owners, and Dev team members to decompose solutions into Epics, leading design and planning of these components. Drive the migration of existing data processing workflows to the Lakehouse architecture, leveraging Iceberg capabilities. Communicates complex technical information clearly, tailoring messages to the appropriate audience to ensure alignment. Key Skills Deep technical knowledge of data engineering solutions and practices. Implementation of data pipelines using AWS data services and Lakehouse capabilities. Highly proficient in Python, Spark and familiar with a variety of development technologies. Skilled in decomposing solutions into components (Epics, stories) to streamline development. Proficient in creating clear, comprehensive documentation. Proficient in quality assurance practices, including code reviews, automated testing, and best practices for data validation. Previous Financial Services experience delivering data solutions against financial and market reference data. Solid grasp of Data Governance and Data Management concepts, including metadata management, master data management, and data quality. Educational Background Bachelors degree in computer science, Software Engineering, or related field essential. Bonus Skills A working knowledge of Indices, Index construction and Asset Management principles.,