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Key job responsibilities
- Implement data ingestion routines, both real time and batch, using best practices in data modeling.
- Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions that work well within the overall data architecture.
- Participate in the full development life cycle, from design, implementation and testing, to documentation, delivery, support, and maintenance.
- Produce comprehensive, usable dataset documentation and metadata.- Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
- Tune application and query performance using profiling tools.- Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for datasets.
Seattle, WA, USA
- 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)
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
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