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Karthik Rajamani

Currently, one of the key imperatives for enterprises to flourish is data analytics, and it takes a lot of collaborative data management and cross-functional analytics for the organizations to be data-centric.

Enter DataOps, an evolving methodology that integrates data, team, tools, and processes to become an efficient and a successful data-driven organization.

Before we start detailing the merits of a career in DataOps, let us catch a glimpse of the technology landscape in the past one and a half decades. An expert in web technologies such as .NET or Java circa was the most sought-after candidate until 2005 from a career standpoint. However, the prospects for this candidate had dwindled by 2015, as by then, there were a few lakh Java or .NET experts. By the start of the last decade, big data had emerged significantly. Additionally, the developers in demand by 2015 were the ones who knew how to work with Hadoop, Hive, Impala, Pig, or Spark.

Now, at the start of this decade, DataOps is one of the trending technologies that’s poised to take off. Data is regarded as the new oil, and rightly so. Hence global enterprises are trying to harness its enormous benefits. Big data systems help us work with a large amount of data. Cloud is for future storage requirements while Containers and DevOps aid us in working with data at a faster pace. But what do we do with the data in the legacy enterprise warehouses? Do they need to be discarded? Certainly not. So, how do we transfer it to the cloud? This is where DataOps comes to our rescue.

One company that has become synonymous with DataOps is StreamSets. Their products such as Control Hub, Data Collector, and Data Transformer have revolutionized the way we can work with data. Their products have democratized the data. A developer, a business analyst, a DBA, a data scientist, or anyone even with no coding background can easily pull data from various databases, move it to big data lake or cloud data lake, and start working on AI/ML models, Excel or tableau reports, etc. If you are a passionate data engineer, you can leverage your Scala/Python/SparkSQL skills to do complex transformations using Streamsets Transformer in a much faster and easier way.

All of this sounds too interesting to be true, doesn’t it? Trust me, while it is interesting, it is also easy to learn and work it too. So, here’s the big question: Are you willing to learn a technology that is taking the market by storm? It is even more encouraging to learn DataOps given that while there is a huge demand for it, there are very few developers across the world.

Here are some exciting positions at TCS to further your career in DataOps.

  • Data Engineer

  • Data Architect

  • Streamsets Developer

  • Platform Engineer

  • Platform Architect

The TCS opportunities in DataOps are enriching if you’re looking to build a fulfilling career in information technology. TCS employees get a chance to upskill themselves in DataOps via in-house training. They also get to deploy learnings derived therein, in a real-time project. We are partnering with several customers across geographies to scale up with DataOps. You too can reap the abundant benefits of a DataOps career by joining the TCS family. To know more about fulfilling as well as rewarding opportunities, keep watching https://ibegin.tcs.com/iBegin/.

It would be great to know your thoughts and insights on this blog. Do send us your views via an email to careers@tcs.com.

We wish you the very best in your career.

About the author

Karthik Rajamani
Currently a Product Manager for TCS Analytics & Insights, Karthik Rajamani has donned various hats in the last 15 plus years in the IT industry. He’s been a Developer, Technical Lead, Lead Support Engineer, Project Manager, IT Business Analyst, Data Analyst, Data Engineer, Citizen Data Scientist, Product Evangelist, Tools Admin to name a few. A B.Tech in IT, Karthik has worked across Public Services, Hi-Tech, Life Sciences, Health Care, and BFSI industry verticals. He loves reading, learning new languages as well as learning about different cultures, and working with people to bring a multi-dimensional view to a problem. He believes in providing simple solutions, keeping the end-user in mind.
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