We’re looking for Data Engineer to help us grow our Data Lake and Data Warehouse Systems, which is being built using a serverless architecture, with 100% native AWS components including Redshift Spectrum, Athena, S3, Lambda, Glue, EMR, Kinesis, SNS, CloudWatch and more! We own a world-class data lake that is used to drive multi-billion dollar decisions on a regular cadence and we're looking to improve on filling the lake quickly, with as little human intervention needed and democratize the data in the lake.

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We’re looking for Data Engineer to help us grow our Data Lake and Data Warehouse Systems, which is being built using a serverless architecture, with 100% native AWS components including Redshift Spectrum, Athena, S3, Lambda, Glue, EMR, Kinesis, SNS, CloudWatch and more! We own a world-class data lake that is used to drive multi-billion dollar decisions on a regular cadence and we're looking to improve on filling the lake quickly, with as little human intervention needed and democratize the data in the lake.

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Key job responsibilities

• Develop and maintain automated ETL pipelines (with monitoring) using scripting languages such as Python, Spark, SQL and AWS services such as S3, Glue, Lambda, SNS, SQS, KMS.

• Implement and support reporting and analytics infrastructure for internal business customers.

• Develop and maintain data security and permissions solutions for enterprise scale data warehouse and data lake implementations including data encryption and database user access controls and logging.

• Develop data objects for business analytics using data modeling techniques.

• Develop and optimize data warehouse and data lake tables using best practices for DDL, physical and logical tables, data partitioning, compression, and parallelization.

• Develop and maintain data warehouse and data lake metadata, data catalog, and user documentation for internal business customers.

• Work with internal business customers and software development teams to gather and document requirements for data publishing and data consumption via data warehouse, data lake, and analytics solutions.

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Basic Qualifications

- 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)
- Bachelor's degree in Computer Science, Computer Engineering, or related fields

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Preferred Qualifications

- 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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