• Looking for Big Data Engineer with 3+ years of experience. • Hands-on experience with MapReduce-based platforms, like Pig, Spark, Shark. • Hands-on experience with data pipeline tools like Kafka, Storm, Spark Streaming. • Store and query data with Sqoop, Hive, MySQL, HBase, Cassandra, MongoDB, Drill, Phoenix, and Presto. • Hands-on experience in managing Big Data on a cluster with HDFS and MapReduce. • Handle streaming data in real time with Kafka, Flume, Spark Streaming, Flink, and Storm. • Experience with Azure cloud, Cognitive Services, Databricks is preferred.
Description Auzmor is US HQ’ed, funded SaaS startup focussed on disrupting the HR space. We combine passion, domain expertise and build products with focus on great end user experiences We are looking for Technical Architect to envision, build, launch and scale multiple SaaS products What You Will Do: • Understand the broader strategy, business goals, and engineering priorities of the company and how to incorporate them into your designs of systems, components, or features • Designing applications and architectures for multi-tenant SaaS software • Responsible for the selection and use of frameworks, platforms and design patterns for Cloud based multi-tenant SaaS based application • Collaborate with engineers, QA, product managers, UX designers, partners/vendors, and other architects to build scalable systems, services, and products for our diverse ecosystem of users across apps What you will need • Minimum of 5+ years of Hands on engineering experience in SaaS, Cloud services environments with architecture design and definition experience using Java/JEE, Struts, Spring, JMS & ORM (Hibernate, JPA) or other Server side technologies, frameworks. • Strong understanding of architecture patterns such as multi-tenancy, scalability, and federation, microservices(design, decomposition, and maintenance ) to build cloud-ready systems • Experience with server-side technologies (preferably Java or Go),frontend technologies (HTML/CSS, Native JS, React, Angular, etc.) and testing frameworks and automation (PHPUnit, Codeception, Behat, Selenium, webdriver, etc.) • Passion for quality and engineering excellence at scale What we would love to see • Exposure to Big data -related technologies such as Hadoop, Spark, Cassandra, Mapreduce or NoSQL, and data management, data retrieval , data quality , ETL, data analysis. • Familiarity with containerized deployments and cloud computing platforms (AWS, Azure, GCP)
To introduce myself I head Global Faculty Acquisition for Simplilearn. About My Company: SIMPLILEARN is a company which has transformed 500,000+ carriers across 150+ countries with 400+ courses and yes we are a Registered Professional Education Provider providing PMI-PMP, PRINCE2, ITIL (Foundation, Intermediate & Expert), MSP, COBIT, Six Sigma (GB, BB & Lean Management), Financial Modeling with MS Excel, CSM, PMI - ACP, RMP, CISSP, CTFL, CISA, CFA Level 1, CCNA, CCNP, Big Data Hadoop, CBAP, iOS, TOGAF, Tableau, Digital Marketing, Data scientist with Python, Data Science with SAS & Excel, Big Data Hadoop Developer & Administrator, Apache Spark and Scala, Tableau Desktop 9, Agile Scrum Master, Salesforce Platform Developer, Azure & Google Cloud. : Our Official website : www.simplilearn.com If you're interested in teaching, interacting, sharing real life experiences and passion to transform Careers, please join hands with us. Onboarding Process • Updated CV needs to be sent to my email id , with relevant certificate copy. • Sample ELearning access will be shared with 15days trail post your registration in our website. • My Subject Matter Expert will evaluate you on your areas of expertise over a telephonic conversation - Duration 15 to 20 minutes • Commercial Discussion. • We will register you to our on-going online session to introduce you to our course content and the Simplilearn style of teaching. • A Demo will be conducted to check your training style, Internet connectivity. • Freelancer Master Service Agreement Payment Process : • Once a workshop/ Last day of the training for the batch is completed you have to share your invoice. • An automated Tracking Id will be shared from our automated ticketing system. • Our Faculty group will verify the details provided and share the invoice to our internal finance team to process your payment, if there are any additional information required we will co-ordinate with you. • Payment will be processed in 15 working days as per the policy this 15 days is from the date of invoice received. Please share your updated CV to get this for next step of on-boarding process.