Amazon Data Engineer 

India, Karnataka, Bengaluru 

945103738

External job descriptionYou are a talented, enthusiastic, and detail-oriented Data Engineer, Data Science, Business Intelligence, or Software Development who knows how to take on big data challenges in an agile way. Duties include big data design and analysis, data modeling, and development, deployment, and operations of big data pipelines. You will also help hire, mentor, and develop peers in the the Music Data Experience team including Data Scientists, Data Engineers, and Software Engineers. You'll help build Amazon Music's most important data pipelines and data sets, and expand self-service data knowledge and capabilities through an Amazon Music data university.Key job responsibilities
Build Data Platform and Data Lake solutions
Build Data Engineering tools
Build real time and micro batch data pipelinesAbout the team
The Music Data eXperience (MDX) team is responsible for the definition, design, production, and quality of foundational datasets consumed by the whole org, data management tools, and the self-service data lake and warehouse platforms on which these datasets are published, stored, shared, and consumed for analytics and science modeling. MDX is split into two sub teams *PARAM* (Platform Architecture Research and AutoMation) and *IDEA* (Intelligence, Data Engineering & Analytics). Data Platform (PARAM) team owns the self-service data lake Data EXchange Store (DEX) and Data Warehouse platforms, builds tools and frameworks for efficient data management, and owns the orchestration and configuration platform for data pipelines. Data Engineering (IDEA) Team owns the foundational data model and datasets, the Spark and Datanet ETL jobs and business logic to build them, away team support for datasets, org wide launch support (when required), the Executive Daily Summary (EDS), and future batch dataset data quality frameworks.

- 1+ years of data engineering experience
- Experience with SQL
- Experience with data modeling, warehousing and building ETL pipelines
- 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 big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.