Fractal is one of the most prominent players in the Artificial Intelligence space. Fractal’s mission is to power every human decision in the enterprise and uses the power of AI to help the world’s most admired Fortune 500 companies.
Our products include Qure.ai to assist radiologists make better diagnostic decisions, Cuddle.ai to assists CEOs and senior executives make better tactical and strategic decisions, Theremin.ai to improve investment decisions and Eugenie.ai to find anomalies in high velocity data.
We have consistently been rated as India’s best companies to work for, by The Great Place to Work® Institute. Fractal has been featured as a leader in the Customer Analytics Service Providers Wave™ 2019 by Forrester Research, and recognized as an “Honorable Vendor” in 2019 magic quadrant for data & analytics by Gartner.
If you are an extraordinary developer who loves to push the boundaries to solve complex business problems using creative solutions, then we wish to talk with you. As an Analytics Technology Engineer, you will work on the Technology team that helps deliver our Data Engineering offerings at large scale to our Fortune clients worldwide. The role is responsible for innovating, building and maintaining technology services.
- Be an integral part of large scale client business development and delivery engagements
- Develop the software and systems needed for end-to-end execution on large projects
- Work across all phases of SDLC, and use Software Engineering principles to build scaled solutions
- Build the knowledge base required to deliver increasingly complex technology projects
Qualifications & Experience
- A bachelor’s degree in Computer Science or related field with 3-10 years of technology experience
- Strong experience in System Integration, Application Development or Data-Warehouse projects, across technologies used in the enterprise space
- Software development experience using:
- Object-oriented languages (e.g. Python, PySpark, Java, C#, C++ ) and frameworks (e.g. J2EE or .NET
- Database programming using any flavours of SQL
- Expertise in relational and dimensional modelling, including big data technologies
- Exposure across all the SDLC process, including testing and deployment
- Expertise in Microsoft Azure is mandatory including components like Azure Data Factory, Azure Data Lake Storage, Azure SQL, Azure DataBricks, HD Insights, ML Service etc.
- Good knowledge of Python and Spark are required
- Good understanding of how to enable analytics using cloud technology and ML Ops
- Experience in Azure Infrastructure and Azure Dev Ops will be a strong plu
- Proven track record in keeping existing technical skills and developing new ones, so that you can make strong contributions to deep architecture discussions around systems and applications in the cloud (Azure, AWS or GCP)
- Characteristics of a forward thinker and self-starter
- Ability to work with a global team of consulting professionals across multiple projects
- Knack for helping an organization to understand application architectures and integration approaches, to architect advanced cloud-based solutions, and to help launch the build-out of those systems
- Passion for educating, training, designing, and building end-to-end systems for a diverse and challenging set of customers to success
Education Qualification:B.E / B.Tech, BCA, MCA equivalent