Mu Sigma - Project Manager - Data Warehousing/Data Engineering (7-10 yrs)
Mu Sigma Business Solutions Pvt. Ltd
Big Data tops many a list of business priorities, thanks to its growing volume, velocity, and variety. However, it is not data, but change that is the cause of anxiety to organization, bringing with it greater complexity and more data.
The challenge here is that analytical thinking isn- t keeping pace with the rate of change in business. This is where we come in - we address the gaps.
Mu Sigma is one of the world's largest Decision Sciences and analytics firm. We help over 140 Fortune 500 clients, across 10 industry verticals, to institutionalize data-driven decision making, and to harness Big Data. We provide our clients with a holistic ecosystem of proprietary technology platforms, processes and people. This ecosystem helps us scale the use of our unique interdisciplinary approach of combining math, business, technology, behavioral science and design thinking to operationalize Decision Science as opposed to Data Science.
Our unique approach to problem solving using cross-industry expertise corroborates our sustainable engagement model with our clients still further, making us one of the most preferred analytics and Decision Sciences partners.
With over 3500 Decision Sciences professionals, we pride in being a category and career defining company. As we continue to scale, we are also looking at hiring the right talent across various levels in our organization. Our unique talent management philosophy has been critically acclaimed by the likes of Harvard Business Review.
- To manage a Datawarehousing/Data Engineering project end to end.
- Ability to understand the technology challenges and architecture.
- To manage the customer expectations and communications.
- Should manage technology projects in data engineering, full stack, web development as needed.
- But focus will be on data warehousing/Data engineering work.
- Should have atleast 7-8 years of overall experience in IT industry.
- Atleast 3-4 years in the Big Data and Data Engineering space.
- Should have managed a team of atleast 10-20 people
- Should have excellent customer facing skills and communications.
- Should have very good exposure on latest Big Data stack like Hadoop, Kafka, Spark etc.
- Exposure to the cloud stack on data engineering is an added benefit.
- Exposure to full stack development like Java, Angular, Django and other tools is a benefit.