Excellent opportunity for Data Engineers to be part of Cognizant’s Intelligent Process Automation practice. It combines advisory services with deep vendor partnerships and integrated solutions to create and execute strategic roadmaps.
Key Responsibilities:
1. Gather business requirements, perform detailed analysis, and produce associated functional specifications across multiple functions.
2. Architect, design, cost, and plan solutions that will support delivery teams as those solutions are implemented into live services.
3. Skilled in writing SQL, Python, and R to analyze data.
4. Develop Subject Matter Expertise on the key data elements.
5. Responsible for liaising between business users and technologists to exchange information in a concise, logical, and understandable way in coordination with the Technology team.
6. Ensuring proper development life cycle is followed with artifacts to support Internal Audit and any inquiries.
7. Consult with users and clients to solve complex system issues/problems through in-depth evaluation of business processes, systems, and industry standards and recommend solutions.
8. Support systems change processes from requirements through implementation and provide input based on analysis of information.
9. Consult with business clients to determine system functional specifications and provide user and operational support.
10. Identify and communicate risks and impacts, considering business implications of the application of technology to the current business environment.
11. Ability to operate with a limited level of direct supervision.
12. Demonstrated ability to work under pressure to meet tight deadlines and approach work methodically with attention to detail.
13. Work with Data Governance and Quality teams to understand data issues.
14. Work with various technology leads to ensure the gaps in the data completeness or accuracy are converted into prioritized Book of Work items.
15. Provide regular updates to senior management in technology, middle office, and front office.
16. Training of relevant teams prior to go-live of new business processes/products, functionality, or applications.
17. Go-live support and investigation of issues.
Essential Experience:
1. Providing database engineering and data delivery to support during application development, working closely with application teams.
2. Data Engineering to ingest, cleanse, and collate data from a wide range of internal and external sources.
3. Creation of reconciliations of data sets.
4. Building analytical models to support reporting and analytics.
5. Creation of reports and analytics.
6. Experience facilitating workshops and discussions to effectively gather requirements and understand the client’s business challenges.
7. Able to produce proposed implementation plans for data analysis work, including estimated effort and technical implications of data insight products.
8. Able to review and comment on data models, pointing out defects and suggesting improvements.
9. Clear written and verbal communications; able to communicate with a wide range of people.
10. Strong leadership, analytical, and communication skills with a passion for data-driven decision making and for establishing best practices.
11. Line management experience; able to give feedback and mentor more junior colleagues.
Qualifications:
1. Experience working with Azure, AWS, or Google Cloud.
2. Experienced in IT architecture and software development lifecycles.
3. Experienced with structured and unstructured data.
4. Experience in combining qualitative and quantitative datasets.
5. Experienced in programming languages such as Python and/or R, and data visualization tools such as Tableau.
6. Experience working with large datasets.
7. Experience in creation of B/FRDs; good documentation and communication with the technology team to provide requirements and understanding of any issues is paramount.
8. Relevant experience in data-related topics: data warehousing, data governance, data quality, data profiling, master data management, ETL, etc.
9. Data modeling, from contextual through to logical and physical modeling skills.
10. Very strong Excel, SQL, Python, and JIRA skills.
11. Excellent communication skills; structured and organized.
12. Excellent stakeholder and management reporting skills.
13. Experience with project planning and tracking, including agile software (i.e., JIRA).
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