Company: Aditya Birla Group
About Company : A global conglomerate, the Aditya Birla Group is in the League of Fortune 500. Anchored by an extraordinary force of over 120,000 employees belonging to 42 nationalities, the Group is built on a strong foundation of stakeholder value creation. With over seven decades of responsible business practices, our businesses have grown into global powerhouses in a wide range of sectors – metals, pulp and fibre, chemicals, textiles, carbon black, telecom and cement. Today, over 50% of Group revenues flow from overseas operations that span 36 countries in North and South America, Africa and Asia.
We believe in nurturing our biggest asset – our people. The Aditya Birla Group was named the AON best employer in India for 2018 – the 3rd time over the last 7 years. The Group ranked 4th in the world and 1st in Asia Pacific in the ‘Top Companies for Leaders’ study 2011, conducted by Aon Hewitt, Fortune Magazine and RBL (a strategic HR and leadership advisory firm).
Website: www.adityabirla.com
Position: Data Engineer
Experience: 3-5 years
Job Locations: Karnataka
Salary: Best In Industry
Eligibility Criteria :
- BE/ B.Tech
- 3-5 years of experience.
Job Purpose:
- Data Engineering – Enterprise Data Engineer who builds Data Lakes, Warehouses, and Pipelines. The Enterprise Data lake/Warehouse will be used to Manage Data and feed BI, Reporting, and Analytics.
- Given our journey towards Cloud, and modernization of Data Platform, it is imperative to have skillsets in Cloud and modern data engineering. Currently, the Central Data and Analytics team has Engineers whose predominant skill is on-premises Teradata. With Teradata reaching the end of its life, the need to migrate to the cloud is now put on the fast track. We will need an employee who can anchor this migration effort and help modernize the Data and Analytics stack.
- Modernize Data Platform – Introduce new Data Engineering tools
- Support Data integration projects – Integration with third-party vendors
- Improve efficiency of ETL and Data Warehouse – By adopting latest DI Tools and techniques
- Anchor Data Lake and other initiatives.
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