Senior Data Platform Engineer

You will be part of: Myntra Data Platform - Analytics 

Myntra is a one stop shop for all your fashion and lifestyle needs. Being India's largest online store for fashion and lifestyle products, Myntra.com aims at providing a hassle free and enjoyable shopping experience to shoppers across the country with the widest range of brands and products on offer. The brand is making a conscious effort to bring the power of fashion to shoppers with an array of the latest and trendiest products available in the country.

Myntra's cloud based big data platform is highly scalable and processes over 7 billion events per day. We are on a journey to modernize our data platform and offer multiple self-serve offerings for Myntra's data consumers. We use the best-of-breed open source components and SaaS solutions as starting points to build out these capabilities along with maintaining critical core data assets of the organization.  

If you are interested in the fast growing field of big data and analytics, and want to work on big data engineering at scale, building data products and building analytical models (Insights) to power business decisions, then this is the team for you. 

Data has become the new currency in the modern day businesses and we are seeing the emergence of new businesses solely built on data. Organizations world over are realizing the potential that their in-house data holds and are increasingly using it in quite creative ways to unlock hidden opportunities. "Data drives decisions" is one of Myntra's core value and is a reflection of how dearly we value data in taking decisions across the organization.

Why is data challenging and how would I contribute?

• There are two fundamental challenges that need to be dealt with. Quantity being the primary issues wherein more and more data is getting created on a daily basis and quality being the other. Data platforms help in ingestion, processing and reporting out of these large data sets. Adaptable, scalable and sustainable platform solutions are essential for Myntra to scale and make data driven decisions. 
• Myntra Data Platform has a multi-petabyte data lakehouse. You will have the opportunity to work and build robust systems around data lakehouse architecture for upcoming critical business initiatives for Myntra. 

What makes this opportunity unique?

• We are a motivated and small team discovering patterns in data and applying to fashion e-commerce to significantly enhance the user experience. Myntra is growing very fast and we need to build scalable and best of the breed engineering systems. Some qualities we are looking for - quick learner, able to work with ambiguous problem statements, ability to come up with clean software designs, code and solutions.

Data platform team Responsibilities: 

• Build and integrate robust data processing pipelines for enterprise-level business analytics.
• Write maintainable/scalable code. Set up and maintain CI/CD pipelines for automated testing and deployment. Advocate best practices on SDLC to team and ensure their implementation.
• Conduct performance testing, troubleshooting and tuning as required. Evaluate the trade-off to choose the right technology. Strong design documentation skills.  
• Help architect data processing pipelines on Big Data systems. Have an ability to identify backend source pipe issues, and collaborate with Tech Engineering to fix these issues.
• Strong engineering mindset - build automated monitoring, alerting, self healing capabilities. Review the design and implementation in collaboration with Architects. 
• Understand the business domain to create reusable cross functional modules. 
• Work closely with Tech Engineering and Product teams to understand their business needs and translate them to platform solutions
• Help resolve data issues, troubleshoot system problems and as needed, assist other staff with reporting and debugging data accuracy issues 

Desired Skills and Experience: 

• Hands on experience with building end to end, complex & robust Big Data Engineering pipelines on Spark (preferably Databricks). Understand the tuning parameters and trade offs involved in configuring distributed processing pipelines. 
• Understanding of Architecture and Design of Data Engineering products 
• Experience in data modeling principles/methods including conceptual, logical & physical Data Models
• Collaborating with business users (tech and non-tech) and designing Data Engineering solutions on Data Lakehouse 
• Proficiency in performance tuning, load testing and certification of code
• Hands on experience working with MPP Databases like Druid, Azure synapse
• Experience in either of the programming languages like Scala, Java and Python