Read the Job Description: Start by carefully reading the job description. Make sure you understand what the job involves.
Check Your Skills: Compare the skills they're looking for with what you know how to do. Figure out where you're strong and where you might need to learn more.
Check Eligibility Criteria: Look at the qualifications they want, like education and experience. Make sure you have what they're asking for.
Update Your Resume and Cover Letter: Change your resume and cover letter to match the job. Highlight the things that make you a good fit.
Learn About the Company: Take some time to find out about the company you want to work for. Understand what they do and what they care about. This helps you show you're interested in them.
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.
Data Intelligence team Responsibilities:
- Build and integrate robust data processing pipelines for enterprise-level business analytics.
- 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 (restartability/graceful failures) features while building the consumption pipelines
- Understand the business domain to create reusable cross functional data assets
- Own the creation, accuracy and quality of consumption pipelines.
- Work closely with Tech Engineering and Product teams to integrate BI solutions and algorithms into the Big Data Platform.
- Help resolve data issues, troubleshoot system problems and as needed, assist other staff with reporting, debugging data accuracy issues and other related functions.
- Build front-end visualization using available BI tools in line with business requirements.
Responsibilities:
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.
Skills Required:
- Hands on experience with building end to end, complex & robust Big Data Engineering pipelines on Spark (Databricks) and advanced PL/SQL
- Expertise in data modeling principles/methods including conceptual, logical & physical Data Models
- Proven data analytics expertise with ability to be Data Domain / Subject matter expert and leverage opportunities to maximize data potential
- Understanding of Architecture and Design of Data Engineering products
- Excellent skills in collaborating with business users (tech and non-tech) and designing Data Engineering solutions on Data Lakhouse & Data Warehouse
- Ability to utilize Business Intelligence tools (Power BI) to represent insights
- Proficiency in performance tuning - spark & pl/sql
- Hands on experience working with MPP Databases like SQL Server, Azure Synapse
- Exposure to programming languages like unix and python is good to have
Eligibility Criteria:
1)Any Graduate
2)Year of Passing: 2014 to 2024
Location: Bangalore