Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients' most complex digital transformation needs.
We leverage our holistic portfolio of capabilities in consulting, design, engineering, operations, and emerging technologies to help clients realize their boldest ambitions and build future-ready, sustainable businesses.
A company recognized globally for its comprehensive portfolio of services, strong commitment to sustainability and good corporate citizenship, we have over 250,000 dedicated employees serving clients across 66 countries.
We deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world.
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• A PROUD HISTORY OF OVER 75 YEARS
• FY22 REVENUE 10.4 BN USD
• WE'RE PRESENT IN 66 COUNTRIES
• OVER 1,400 ACTIVE GLOBAL CLIENTS
Location: Open for Austin, TX
and
Sunnyvale, CA
Requirements:
- Spark
- Scala
- Big data databases - like HBase etc
- PySpark
- Python
- Knowledge of Airflow , Hive etc.. would be good
- Datawarehouse
- AWS - good to have
- Good communication skill
Role and Qualification
- Minimum of 10+ year of experience designing and implementing a full-scale data warehouse solution.
- A minimum of Six years' experience in developing using Spark, Scala .
- A highly effective communicator, both orally and in writing
- Problem-solving and architecting skills in cases of unclear requirements.
The potential compensation for this role is based on labor costs in local markets, as well as the job-related skills, knowledge and experience of the candidate. Expected base pay for this role ranges from [$80,000 to $1,58,000 for Austin, TX and $80,000 to $1,73,800 for Sunnyvale, CA ]. Based on the position, the role is also eligible for Wipro's standard benefits and additional compensation offerings, including a full range of medical and dental benefits options, disability insurance, paid time off (inclusive of sick leave), other paid and unpaid leave options as well as potential incentive or variable compensation.
Data Analysis