Vikas Dwivedi

Define/develop Big Data technologies, platforms and applications; Develop scalable, robust systems that will be highly adaptable to changing business needs; Design, improve, and scale applications to the next level; Interface with application owners, developers and project managers.

Designing, integrating and documenting technical components for data flows or applications that perform analysis at a massive scale; Build and maintain a robust data engineering process to develop and implement self-serve data and tools for data scientists; Implement platforms, workflows and dashboards to deliver automated status reporting on governance, policy compliance and security risks across all business unit; Implemented Risk data analytics platform based on predictive data model; Implement Data Quality (DQ) rules provided.

Provide analytical insights into problems, emerging trends and changes to portfolio; Drive projects end to end from ideation to implementation in a time sensitive and efficient manner; Identify new opportunities and continuous improvement to contribute to the team’s KPIs and targets.

Gather requirements, develop specifications and lead project execution; Design, implement and support efficient & reliable data pipelines to move data from a wide variety of data sources to our data warehouses/data lake; Design and implement data aggregation, cleansing and reporting layers; Work cross functionally with analysts, product managers and BU/FG teams to build systems for effective data exploration and consumption.

Develop and automate high-performance data processing systems to drive business growth and improve the product experience; Work with cross-functional teams to enable data insights through Data lifecycle; Build large-scale batch and real-time data pipelines with data processing frameworks using Spark.