Become a Data Engineer – The Fastest Growing Tech Career In The World; Join The Industry-Supported Praxis Post-Graduate Program in Data Engineering
Why should you pursue the Praxis Post-Graduate Program in Data Engineering? The demand for Big Data professionals – data scientists, data engineers, ML engineers – has seen explosive growth in recent times – and this has further accelerated due to the rapid COVID-driven digitalisation. The availability of trained resources, however, has not been able to keep pace with the demand. This presents a great opportunity for professionals to learn these skills and build exciting and rewarding careers. Praxis Business School is a well-known name in the big data professional space – we have pioneered the formal teaching of business analytics/ data science in the country and our post graduate program in data science is ranked 2 in the country by AIM this year (and has been consistently ranked in the top 3 for the past 5 years). According to the DICE tech job report of 2020, Data Engineering (DE) is the fastest-growing tech job with a nearly 50% year-on-year growth. Driven by this explosion in the demand for data engineers, and several conversations we have had with their data science program recruiters, we have decided to launch a 6-month, full-time, in-class post graduate program in Data Engineering at our Bangalore campus starting February-end this year. What do Data Engineers do? Data engineers set up and maintain the data infrastructures that support business information systems and applications. They design, build and install scalable data pipelines – this includes collection, processing, storing and transforming of data into formats that can be processed and analysed. According to Jesse Anderson, managing director of the Big Data Institute, data engineers are professionals who have specialised their skills in creating software solutions around big data. To create data pipelines at big data scale, data engineers are required to bring together in-depth understanding of up to around 30 technologies and frameworks and choose the right combination of these technologies and tools to serve specific business requirements. They have to make sure that the data is clean, reliable and ready for use. How are Data Engineers different from Data Scientists? Data Scientists combine domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. They also present the results of their analyses using data visualisation techniques. Data engineers, on the other hand, execute the data strategy of the organisation, which means creating the infrastructure and processes for identifying, storing, provisioning, processing and governing the data assets. Data engineers build data platforms that enable data scientists to analyse data and train machine learning models. What skills do Data Engineers need? A data engineer should have advanced programming and systems creation skills. In addition to programming proficiency in Python, Java/ Scala and SQL, a data engineer needs to acquire the skills in the following core areas: cloud, distributed systems, databases, data warehousing, data processing, real-time data ecosystem, data orchestration, data science and ML (basics), full-stack development – and the associated technologies. The big data ecosystem is evolving at a staggering speed, driven and supported by new technologies. Data engineers have to be adept at quickly understanding and using new technologies – this requires them to be good learners and quick adopters. They also need to be good at collaborating and communicating, as their work requires them to interact with different stakeholders and work closely with them. The 6-month full-time Praxis Post Graduate Program in Data Engineering The Data Engineering programme at Praxis is designed to create professionals who become day-one productive for the organisation. The program equips professionals with the know-how of existing tools and technologies for Data Management & Data Modelling and introduces them to the paradigms of Distributed Systems and Cloud Computing. The participants get to work on a Capstone Project that requires them to migrate data to Big-Data platforms and manage the system on the Cloud. The program is divided into three trimesters of two-months each covering working with traditional dataengineering platforms for big data andrunning enterprise business on cloud The pedagogy comprises design of a contemporary and relevant curriculum, delivery which is a blend of classroom lectures, use case discussions and hands-on labs, and assessment based on tests, assignments and projects. Capstone Project A critical part of the learning process is the Capstone Project which gives students the opportunity to apply their classroom learnings to real world challenges faced by business. Some examples of capstone projects could be – Migration of a Traditional Data Warehouse to a Cloud Data Lake; Building an Orchestrated Application on the Cloud for managing Sensor-Data; Real-time Streaming Feeds analysis and Visualisation using a combination of Kafka, Storm and real-time Data visualisation tool. Learning outcomes Participants of this program will be able to: Re-engineer Enterprise Data Architecture without hampering BAU (business as usual)Work with relational and NoSQL data modelsCreate scalable and efficient data warehousesWork efficiently with massive datasetsBuild and interact with a Cloud-based Data WarehouseAutomate and monitor data pipelinesDevelop proficiency in Stream Processing using Cloud Data LakeSolve the appropriate use cases using big data technologies Industry partnerships – Genpact and LatentView The Praxis data engineering program has been designed and developed with the invaluable inputs from its two knowledge partners, Genpact and LatentView. Leading practitioners from these enterprises have collaborated with the Praxis faculty team to create a program that meets the contemporary industry requirements and enables the participants to transition into this career with capability and confidence. Placements Placements are a natural outcome of doing a few things right – the right course curriculum, the right delivery pedagogy, and the right industry partnerships. The Praxis Placement Program is a structured process committed to creating quality placement opportunities for all enrolled students. It has had a consistently 90% + placement record for its data science program and the placement team has already tied-up with prospective recruiters for the date engineering program. On an average, for every data scientist in the team, an organisation requires 4-5 data engineers. Thus, there are plenty of exciting jobs available if you have data engineering skills. Who should enroll in this course? This course is aimed at facilitating a smooth transition into the domain of data engineering. Candidates who have a technology background, are passionate about technology and are good at programming should seriously look at data engineering as a career option. Fresh graduates with engineering or computer science backgrounds who wish to be part of the big data ecosystem, or people with work experience in the traditional technology areas who want to switch to new age ‘hot’ domains will find this course and a career in data engineering very fulfilling. The course is offered at the Bangalore Campus of Praxis Business School. Eligibility criteria:  A bachelor’s degree in computer sciences. It could be an engineering or a computer applications’ degree. The school also considers non-degree holders with some familiarity with computer systems for enrolment. The course is ideal if you are trying to switch careers within the domain. The total fee for the course is ₹200000 + GST and can be paid in three installments. As a prerequisite, the student needs to have a 64-bit wi-fi enabled personal laptop equipped with a minimum of 6 GB RAM. Praxis has tied up with Credila and Avanse Financial Services to offer loans for students wishing to enroll. As the data industry grows and applications become more sophisticated, the availability of large and well-structured data for building and running machine learning models will become crucial and data engineers will be in high demand. If you plan on studying to become one, Praxis’ program is the perfect opportunity for you. To apply for the PGP in Data Engineering, click here.
Why should you pursue the Praxis Post-Graduate Program in Data Engineering? The demand for Big Data professionals – data scientists, data engineers, ML engineers – has seen explosive growth in recent times – and this has further accelerated due to the rapid COVID-driven digitalisation. The availability of trained resources, however, has not been able to […]
The program equips professionals with the know-how of existing tools and technologies for Data Management & Data Modelling and introduces them to the paradigms of Distributed Systems and Cloud Computing.
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Mr Amit Ghosh is the Director, Marketing &amp; Sales at Praxis Business School. He has an extensive experience of more than 18 years across sectors where he has worked with leading global and Indian companies on large-scale transformational projects.