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06/12 Aravind TR
Associate Principal - Machine Learning/Big Data Analytics at Rinalytics Advisors

Views:2186 Applications:51 Rec. Actions:Recruiter Actions:1

Head - Data Engineering - IT (12-16 yrs)

Bangalore Job Code: 772724

An accomplished data engineering leader with proven experience in architecture and building large scale distributed applications and platform to acquire, process, analyse data in real-time as well batch.

- An ideal candidate is expected to lead 3 member data engineering team and would bring strong data architecture and data engineering expertise.

- Creation & execution of the vision behind the core Data Engineering group through development and deployment of data infrastructure roadmap for the business.

- Play a critical role in the development of the company's Technology roadmap, infrastructure and platform; lead the implementation of DWH and query building technology that aligns with business strategy.

- Provide high-level leadership to the Data Infrastructure/platform development and improve the functionality, reliability, scalability by bringing industry best-practice and technology trends into the continued innovation to Data platform.

- Own and extend the data pipeline through the data collection, data storage, data processing, and data transformation of large data-sets by using DWH, ETL, Redshift and Sql.

Essential Duties &Responsibilities

- Minimum Bachelor's degree in Computer Science, Engineering or Technology.

- 12 -16 years of experience in Data architecture, data engineering, and/or preferably in product development, designing and implementing data architectures, data pipelines for large data sets.

- Strong expertise in BI architectures, Redshift, sql, data warehousing, data modeling, and Big Data.

- Design, develop and deploy state-of-the-art data models, DWH and data pipeline/ETL using emerging technologies and tools

- Define standards, methodologies for Data Warehousing environment and design & build highly scalable data pipelines using new generation tools and technologies like Redshift, DWH and big data to induct data from various platforms.

- Translate critical consumer business insights into scalable technical architectures meeting data warehousing design standards.

Women-friendly workplace:

Maternity and Paternity Benefits

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