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Tier-1 employer and common data-engineer role increase applicant density.
Data engineering skills (SQL, ETL, Spark) are highly transferable across industries.
Moderate due to mandatory technical skills (SQL/Java/C++) despite no explicit years requirement.
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Develop and manage ETL data pipelines to clean, transform, and aggregate raw data for analytics use.
Build, install, and scale database systems including writing complex queries across multiple machines.
Support data retrieval needs for Analysts and Scientists and provide input on data management and quality strategy.
Bachelor’s or Master’s degree in Computer Science or related field.
Proficiency in at least one of the following programming languages: SQL, Java, or C++.
Experience or demonstrated awareness of software development lifecycle including testing, deployment, and releases.
Work Experience Required: Not explicitly mentioned in the JD.
Experience working with big data technologies such as Hadoop (Sqoop, Hive, HBASE, Spark) and programming languages like Python or Scala is a plus.
Familiarity with Agile methodologies such as SCRUM and tools like Azure VSTS is beneficial.
Ability to work independently in a global distributed environment with readiness for cloud and real-time integration projects (Kafka, NiFi, AWS, Google Cloud, or Azure).