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As a Data Engineer, you will be working in one of the world's largest and most complex data warehouse environments. You will design, implement and support scalable data infrastructure solutions to integrate with multi-heterogeneous data sources, aggregate and retrieve data in a fast and safe mode, curate data that can be used in reporting, analysis, machine learning models and ad-hoc data requests. You will be exposed to cutting-edge AWS big data technologies.Key job responsibilities
- Design and develop the pipelines required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Python, and AWS big data technologies.- Oversee and continually improve production operations, including optimizing data delivery, re-designing infrastructure for greater scalability, code deployments, bug fixes and overall release management and coordination.- Establish and maintain best practices for the design, development and support of data integration solutions, including documentation.- Read, write, and debug data processing and orchestration code written in Python/Scala following best coding standards.
- 1+ years of data engineering experience
- 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)
- Knowledge of writing and optimizing SQL queries in a business environment with large-scale, complex datasets
- Bachelor's degree
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
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