2023 Data Engineer Internship

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Job Description

Batch-2023/2024

Key job responsibilities

  • Design, implement, and automate deployment of our distributed system for collecting and processing log events from multiple sources
  • Design data schema and operate internal data warehouses and SQL/NoSQL database systems
  • Own the design, development, and maintenance of ongoing metrics, reports, analyses, and dashboards to drive key business decisions
  • Monitor and troubleshoot operational or data issues in the data pipelines
  • Drive architectural plans and implementation for future data storage, reporting, and analytic solutions
  • Work collaboratively with Business Analysts, Data Scientists, and other internal partners to identify opportunities/problems
  • Provide assistance to the team with troubleshooting, researching the root cause, and thoroughly resolving defects in the event of a problem

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BASIC QUALIFICATIONS

  • Currently enrolled in a Bachelor’s or Master’s degree program in computer engineering, computer science, or a similar technical field
  • Availability to complete an internship minimum 6 months long working full time week
  • Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
  • Experience with one or more scripting language (e.g., Python, KornShell)
  • Experience with data mining, data warehouse solutions
  • Experience with ETL flow and tools

PREFERRED QUALIFICATIONS

  • Master’s or advance technical degree
  • Proficient in at least one or more query language, schema definition language, and scripting language
  • Knowledge of writing and optimizing SQL queries in a business environment with large-scale, complex datasets
  • Experience with data visualization software (e.g., AWS QuickSight or Tableau) or open-source project
  • Experience with big data processing technology (e.g., Hadoop or ApacheSpark), data warehouse technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments
  • Ability to deal with ambiguity in a fast-paced environment