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Big Data Engineer

Job Requirement

  • Installation, configuration and administration of Big Data components (including Hadoop/Spark) for batch and real-time analytics and data hubs
  • Capable of processing large sets of structured, semi-structured and unstructured data
  • Able to assess business rules, collaborate with stakeholders and perform source-to-target data mapping, design and review.
  • Familiar with data architecture for designing data ingestion pipeline design, Hadoop information architecture, data modeling and data mining, machine learning and advanced data processing
  • Optional - Visual communicator – ability to convert and present data in an easy comprehensible visualization using tools like D3.js, Tableau
  • To enjoy being challenged, solve complex problems on a daily basis
  • Proficient in executing efficient and robust ETL workflows
  • To be able to work in teams and collaborate with others to clarify requirements
  • To be able to tune Hadoop solutions to improve performance and end-user experience
  • To have strong co-ordination and project management skills to handle complex projects
  • Engineering background


  • Big Data Ecosystems: Storm, Kafka, Spark, Flink, LogStash, Elastic Search, Solr, Nifi, Zookeeper, Cassandra, Hadoop, Hive, Pig, Sqoop, Oozie, Flume
  • Programming Languages: Java
  • Scripting Languages: JavaScript,D3.js, Python and Bash, R (optional)
  • Databases: NoSQL, SQL
  • Tools: IDE, Git, Maven
  • Platforms: Linux/Unix
  • Application Servers: Apache Tomcat, Node.js
  • Desired Domain Experience : Credit Cards / Banking and Financial Services

Data Scientist

Job Requirement

  • Strong primary expertise as data engineer or data scientist, with the ability to stretch beyond one’s core field of expertise.
  • PhD or Master at least 2+ years *relevant experience* as a strong contributor on a data science team
  • Relevant degree in Statistics, Math / Applied Math, Operations Research, Computer Science, Economics or Quantitative Finance
  • Expertise in at least one analytics function: attribution, segmentation, response modeling, churn, propensity, customer LTV, supply chain / logistics, geospatial inference, recommender systems, causal inference, forecasting, pricing, NLP or image processing
  • Proficiency in a core programming language, such as: Python, C/C++, Scala, Java, Ruby
  • Proficiency in R/Python, particularly to prototype mathematical models
  • Proficiency with SQL and/or NoSQL
  • Proficiency with Tableau, R-Shiny /or other data visualization tools
  • Ability to scope and define data sets needed for specific use cases and identifying data gaps
  • Ability to translate scientific insights into product decisions and work streams
  • Flexibility to handle directional changes and moving priorities to ensure project success
  • Strong oral and written communication skills
  • Strong client management skills – ability to lead and persuade, positive energy, relentless focus on business impact

Nice to have

  • Additional domain knowledge and technical expertise a big plus
  • Experience with AWS or Azure cloud computing environments
  • Proficiency with a distributed computing platform (Hadoop, Spark, etc.)
  • Experience querying and administering big data storage services (Redshift, Teradata, Aurora, DynamoDB, etc.)
  • Experience with general software release cycles / shipping machine learning or predictive analytics models at scale