Data Engineering role at ThoughtWorks ThoughtWorks India is looking for talented data engineers passionate about building large scale data processing systems to help manage the ever-growing information needs of our clients. Our developers have been contributing code to major organizations and open source projects for over 25 years now. They’ve also been writing books, speaking at conferences, and helping push software development forward -- changing companies and even industries along the way. As Consultants, we work with our clients to ensure we’re delivering the best possible solution. Our Lead Dev plays an important role in leading these projects to success. You will be responsible for - Creating complex data processing pipelines, as part of diverse, high energy teams Designing scalable implementations of the models developed by our Data Scientists Hands-on programming based on TDD, usually in a pair programming environment Deploying data pipelines in production based on Continuous Delivery practices Ideally, you should have - 2-6 years of overall industry experience Minimum of 2 years of experience building and deploying large scale data processing pipelines in a production environment Strong domain modelling and coding experience in Java /Scala / Python. Experience building data pipelines and data centric applications using distributed storage platforms like HDFS, S3, NoSql databases (Hbase, Cassandra, etc) and distributed processing platforms like Hadoop, Spark, Hive, Oozie, Airflow, Kafka etc in a production setting Hands on experience in (at least one or more) MapR, Cloudera, Hortonworks and/or Cloud (AWS EMR, Azure HDInsights, Qubole etc.) Knowledge of software best practices like Test-Driven Development (TDD) and Continuous Integration (CI), Agile development Strong communication skills with the ability to work in a consulting environment is essential And here’s some of the perks of being part of a unique organization like ThoughtWorks: A real commitment to “changing the face of IT” -- our way of thinking about diversity and inclusion. Over the past ten years, we’ve implemented a lot of initiatives to make ThoughtWorks a place that reflects the world around us, and to make this a welcoming home to technologists of all stripes. We’re not perfect, but we’re actively working towards true gender balance for our business and our industry, and you’ll see that diversity reflected on our project teams and in offices. Continuous learning. You’ll be constantly exposed to new languages, frameworks and ideas from your peers and as you work on different projects -- challenging you to stay at the top of your game. Support to grow as a technologist outside of your role at ThoughtWorks. This is why ThoughtWorkers have written over 100 books and can be found speaking at (and, ahem, keynoting) tech conferences all over the world. We love to learn and share knowledge, and you’ll find a community of passionate technologists eager to back your endeavors, whatever they may be. You’ll also receive financial support to attend conferences every year. An organizational commitment to social responsibility. ThoughtWorkers challenge each other to be just a little more thoughtful about the world around us, and we believe in using our profits for good. All around the world, you’ll find ThoughtWorks supporting great causes and organizations in both official and unofficial capacities. If you relish the idea of being part of ThoughtWorks’ Data Practice that extends beyond the work we do for our customers, you may find ThoughtWorks is the right place for you. If you share our passion for technology and want to help change the world with software, we want to hear from you!
Job Description: Be responsible for scaling our analytics capability across all internal disciplines and guide our strategic direction in regards to analytics Organize and analyze large, diverse data sets across multiple platforms Identify key insights and leverage them to inform and influence product strategy Technical Interactions with vendor or partners in technical capacity for scope/ approach & deliverables. Develops proof of concept to prove or disprove validity of concept. Working with all parts of the business to identify analytical requirements and formalize an approach for reliable, relevant, accurate, efficientreporting on those requirements Designing and implementing advanced statistical testing for customized problem solving Deliver concise verbal and written explanations of analyses to senior management that elevate findings into strategic recommendations Desired Candidate Profile: MTech / BE / BTech / MSc in CS or Stats or Maths, Operation Research, Statistics, Econometrics or in any quantitative field Experience in using Python, R, SAS Experience in working with large data sets and big data systems (SQL, Hadoop, Hive, etc.) Keen aptitude for large-scale data analysis with a passion for identifying key insights from data Expert working knowledge in various machine learning algorithms such XGBoost, SVM Etc. We are looking candidates from the following: Experience in Unsecured Loans & SME Loans analytics (cards, installment loans) - risk based pricing analytics Experience in Differential pricing / selection analytics (retail, airlines / travel etc). Experience in Digital product companies or Digital eCommerce with Product mindset and experience Experience in Fraud / Risk from Banks, NBFC / Fintech / Credit Bureau Experience in Online media with knowledge of media, online ads & sales (agencies) - Knowledge of DMP, DFP, Adobe/Omniture tools, Cloud Experience in Consumer Durable Loans lending companies (Experience in Credit Cards, Personal Loan - optional) Experience in Tractor Loans lending companies (Experience in Farm) Experience in Recovery, Collections analytics Experience in Marketing Analytics with Digital Marketing, Market Mix modelling, Advertising Technology
• 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.