Inside Sales Associate

1. Big data developer with 8+ years of professional IT experience with expertise in Hadoop ecosystem components in ingestion, Data modeling, querying, processing, storage, analysis, Data Integration and Implementing enterprise level systems spanning Big Data.
2. A skilled developer with strong problem solving, debugging and analytical capabilities, who actively engages in understanding customer requirements.
3. Expertise in Apache Hadoop ecosystem components like Spark, Hadoop Distributed File Systems(HDFS), HiveMapReduce, Hive, Sqoop, HBase, Zookeeper, YARN, Flume, Pig, Nifi, Scala and Oozie.
4. Hands on experience in creating real - time data streaming solutions using Apache Spark core, Spark SQL & DataFrames, Kafka, Spark streaming and Apache Storm.
5. Excellent knowledge of Hadoop architecture and daemons of Hadoop clusters, which include Name node,Data node, Resource manager, Node Manager and Job history server.
6. Worked on both Cloudera and Horton works in Hadoop Distributions. Experience in managing Hadoop clustersusing Cloudera Manager tool.
7. Well versed in installation, Configuration, Managing of Big Data and underlying infrastructure of Hadoop Cluster.
8. Hands on experience in coding MapReduce/Yarn Programs using Java, Scala and Python for analyzing Big Data.
9. Exposure to Cloudera development environment and management using Cloudera Manager.
10. Extensively worked on Spark using Scala on cluster for computational (analytics), installed it on top of Hadoop performed advanced analytical application by making use of Spark with Hive and SQL/Oracle .
11. Implemented Spark using PYTHON and utilizing Data frames and Spark SQL API for faster processing of data and handled importing data from different data sources into HDFS using Sqoop and performing transformations using Hive, MapReduce and then loading data into HDFS.
12. Used Spark Data Frames API over Cloudera platform to perform analytics on Hive data.
13. Hands on experience in MLlib from Spark which are used for predictive intelligence, customer segmentation and for smooth maintenance in Spark streaming.
14. Experience in using Flume to load log files into HDFS and Oozie for workflow design and scheduling.
15. Experience in optimizing MapReduce jobs to use HDFS efficiently by using various compression mechanisms.
16. Working on creating data pipeline for different events of ingestion, aggregation, and load consumer response data into Hive external tables in HDFS location to serve as feed for tableau dashboards.
17. Hands on experience in using Sqoop to import data into HDFS from RDBMS and vice-versa.
18. In-depth Understanding of Oozie to schedule all Hive/Sqoop/HBase jobs.
19. Hands on expertise in real time analytics with Apache Spark.
20. Experience in converting Hive/SQL queries into RDD transformations using Apache Spark, Scala and Python.
21. Extensive experience in working with different ETL tool environments like SSIS, Informatica and reporting tool environments like SQL Server Reporting Services (SSRS).
22. Experience in Microsoft cloud and setting cluster in Amazon EC2 & S3 including the automation of setting & extending the clusters in AWS Amazon cloud.
23. Extensively worked on Spark using Python on cluster for computational (analytics), installed it on top of Hadoop performed advanced analytical application by making use of Spark with Hive and SQL.
24. Strong experience and knowledge of real time data analytics using Spark Streaming, Kafka and Flume.
25. Knowledge in installation, configuration, supporting and managing Hadoop Clusters using Apache, Cloudera (CDH3, CDH4) distributions and on Amazon web services (AWS).
26. Experienced in writing Ad Hoc queries using Cloudera Impala, also used Impala analytical functions.
27. Experience in creating Data frames using PySpark and performing operation on the Data frames using Python.
28. In depth understanding/knowledge of Hadoop Architecture and various components such as HDFS and MapReduce Programming Paradigm, High Availability and YARN architecture.
29. Establishing multiple connections to different Redshift clusters (Bank Prod, Card Prod, SBBDA Cluster) and provide the access for pulling the information we need for analysis. 
30. Generated various kinds of knowledge reports using Power BI based on Business specification. 
31. Developed interactive Tableau dashboards to provide a clear understanding of industry specific KPIs using quick filters and parameters to handle them more efficiently.
32. Well Experience in projects using JIRA, Testing, Maven and Jenkins build tools.
33. Experienced in designing, built, and deploying and utilizing almost all the AWS stack (Including EC2, S3,), focusing on high-availability, fault tolerance, and auto-scaling.
34. Good experience with use-case development, with Software methodologies like Agile and Waterfall.
35. Working knowledge of Amazon's Elastic Cloud Compute( EC2 ) infrastructure for computational tasks and Simple Storage Service ( S3 ) as Storage mechanism.
36. Good working experience in importing data using Sqoop, SFTP from various sources like RDMS, Teradata, Mainframes, Oracle, Netezza to HDFS and performed transformations on it using Hive, Pig and Spark .
37. Extensive experience in Text Analytics, developing different Statistical Machine Learning solutions to various business problems and generating data visualizations using Python and R.
38. Proficient in NoSQL databases including HBase, Cassandra, MongoDB and its integration with Hadoop cluster.
39. Hands on experience in Hadoop Big data technology working on MapReduce, Pig, Hive as Analysis tool, Sqoop and Flume data import/export tools.

• Defining new merchandising or reporting functionality
• Adding more advanced search capabilities
• Improving scoring/recommendation models
• eCommerce platform integrations/API implementations
• Load testing/scaling features as we continuously grow
• Something new. There are always interesting new challenges that come our way. Here are a couple of things we’ve worked on recently:
  • Managing background jobs with competing performance goals like quick turnaround while staying within platform API limits
  • Embedding and dynamically changing products in an email even after sending it
  • Managing and coordinating multi data-center processes

• 1-3 years of experience in Ruby On Rails (or a similar MVC framework like Express or Django). You are comfortable with Routes, Migrations, Models, Callbacks, Validations, and so on.
• Ability to design clean, scalable data structures for new features.
• A good understanding of design patterns so that complex processes are written in a maintainable way.
• Knowledge of managing source code with Git.
• Comfortable in a Linux OS.
• Good communication skills, and ability to clearly plan and describe features before building.

• Challenging, exciting work, at scale
  You get to understand the challenges our customers face first-hand, and collaboratively design and build amazing solutions that will be used by millions of shoppers through billions of API requests. There’s always something new and exciting to build.
• Have a direct impact
  Seven engineers currently build, refine, and scale the entire product. Working in a small team means you will have a say in the way the product is built, and your performance will have a direct impact on the company’s outcome.
• Culture
  Tagalys is a place for you to be yourself, enjoy your work, and achieve your potential. We love the energy that comes from working with smart people in a simple and welcoming environment. We design our workflow to make sure you are also able to focus on everything else in life that is important: family, friends, and health.
• Benefits
  You get great pay, coupled with flexible hours, a hybrid work model, and comprehensive insurance for your and your dependents. For the people contributing significantly, we also offer ESOPs so there is an opportunity to build wealth as you help the company grow.

AWS Data Engineer:

Job Description

• 3+ years of experience in AWS Data Engineering.

• Design and build ETL pipelines & Data lakes to automate ingestion of structured and unstructured data

• Experience working with AWS big data technologies (Redshift, S3, AWS Glue, Kinesis, Athena ,DMS, EMR and Lambda for Serverless ETL)

• Should have knowledge in SQL and NoSQL programming languages.

• Have worked on batch and real time pipelines.

• Excellent programming and debugging skills in Scala or Python & Spark.

• Good Experience in Data Lake formation, Apache spark, python, hands on experience in deploying the models.

• Must have experience in Production migration Process

• Nice to have experience with Power BI visualization tools and connectivity

Roles & Responsibilities:

• Design, build and operationalize large scale enterprise data solutions and applications

• Analyze, re-architect and re-platform on premise data warehouses to data platforms on AWS cloud.

• Design and build production data pipelines from ingestion to consumption within AWS big data architecture, using Python, or Scala.

• Perform detail assessments of current state data platforms and create an appropriate transition path to AWS cloud.

• Develop scalable, secured, and efficient backend for the website, mobile app, and browser extension.
• Integration of user-facing elements developed by front-end developers
• Solve complex performance problems and architectural challenges
• Ensure HTML, CSS, and shared JavaScript is valid and consistent across related applications
• API development for mobile app, browser extension, web
• Design and maintain a database
• Develop components of the database such as storage, queries, and triggers
• Create reusable, effective, and scalable PHP code
• Implement security and data protection measures
• Integration of payment gateway, third-party services via API
• Source code management using bit bucket/git
• Using/creating packages for reusability across the products
• Integration of multiple data sources and databases into one system

Skills we are looking for :

- Experience in developing full-stack applications at scale in ReactJs/AngularJs & NodeJs.

- Strong knowledge and experience in HTML(5), CSS, SCSS, and Advanced JavaScript

- Good knowledge of coding RESTful APIs.

- Strong knowledge of Web Storage (Cookie, Local Storage, and Session Storage)

- Knowledge of modern authorization mechanisms, such as JWT

- Familiarity with modern front-end build pipelines and tools

- Ability to work in a lean-agile development environment.

Good to know :

- Using GIT

- Knowledge of AWS

- Familiarity with GraphQL will be a brownie point