Job Details

Responsibilities

• Proven experience in developing architecture blueprint, design specifications, data interfaces and integration approaches, infrastructure requirements, etc.
• The candidate should have proven experience in technically designing data engineering platforms for multi-geography clients including aspects of data modelling, data integration (ETL), data governance, meta-data management, data security& data quality along with best practice methodologies and industry standards.
• Must have designed end-to-end data modelling solutions for enterprises using ERWIN or similar tools. E.g. MDM, big data, datawarehousing, ODS, client 360, analytics data marts
• Define the technology roadmap for the solution platform with analytical tools, Real Time Decision Management, Hadoop Data Lake, Artificial Intelligence with Machine Learning, and other evolving technologies with integration to SLF systems.
• Must be well versed with architecting data-as-a-service layer for servicing Digital assets, decision support systems (BI), Visualization/reporting & analytics
• Good understanding of architecting data ingestion framework capable of processing structured, semi-structured & un-structured data sets in batch & real time and integrating it with internal data to develop real-time actionable insights
• Well versed with implementing data architecture options including on premise, on-cloud and hybrid options
• Conduct prototyping with the solutions and drive the requirements to closure with the business users.  Able to use “Open Analytics” solutions for quick prototyping, then implement, and operationalize with SLF technologies.
• The incumbent will be an adaptable individual, who enjoys multi-tasking and working with multiple stakeholders to achieve the defined strategic and financial targets
• Experience in setting up data practice or centre of excellence for data is an added advantage

Requirements

• Undergraduate degree in Computer Science, Engineering or related fields.
• Overall 14-17 yrs. of experience in delivering data engineering solutions
• At least 5-7 yrs. of experience as an enterprise data architect
• At least 2-3 years of experience in implementing Hadoop distribution (i.e. Hortonworks or similar) for Big Data analytics
• Solid experience in handling traditional database (i.e. Oracle, SQL, DB2, etc.), ETL (Informatica power center), data / visual modelling tools (e.g. Erwin, Sparx Enterprise Architect, etc), operating systems (i.e. Linux / UNIX and Windows), performing monitoring and tuning.
• Nice to have understanding of Artificial Intelligence solutions covering Machine Learning with automated feedbackFamiliar with architectural terminology and awareness of architectural frameworks (e.g. TOGAF, Zachman, etc.) is an added advantage