Intelliswift
Data Engineer III
Intelliswift, Dallas, Texas, United States, 75215
Job ID: 24-04493Pay rate range - $65/hr. to $70/hr. on W2Dallas is the 1 st preference if not Seattle WA, Arlington, VA
Must HaveSQLPythonData warehousing / Data lake
Years of Experience: 5-7 years
Degree or Certification:BS in engineering
Responsibilities- Plan, design, implement, and manage a deployment of a self-service data platform using native AWS services- Design, build, and maintain data pipelines using modern Big Data technologies such as AWS Redshift, S3, Glue, Athena, EMR, Spark, Hive, etc.- Utilize modern cloud database and storage concepts to for data storage and versioning (Data Lakes with AWS S3)- Establish scalable, efficient, automated processes for large-scale data analysis- Build data pipelines to feed machine learning models for real-time and large-scale offline use cases.- Support the development of performance dashboards that encompass key metrics to be reviewed with senior leadership and sales management- Work with business owners and partners to build data sets that answer their specific business questions
Required Skills & Experience- 5+ years of data engineering experience- Experience with data modeling, warehousing, and building ETL pipelines- Experience with SQL- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS- Experience mentoring team members on best practices
Preferred Skills- Experience with big data technologies such as Hadoop, Hive, Spark, EMR- Experience operating large data warehouses- Experience with Native AWS services
Must HaveSQLPythonData warehousing / Data lake
Years of Experience: 5-7 years
Degree or Certification:BS in engineering
Responsibilities- Plan, design, implement, and manage a deployment of a self-service data platform using native AWS services- Design, build, and maintain data pipelines using modern Big Data technologies such as AWS Redshift, S3, Glue, Athena, EMR, Spark, Hive, etc.- Utilize modern cloud database and storage concepts to for data storage and versioning (Data Lakes with AWS S3)- Establish scalable, efficient, automated processes for large-scale data analysis- Build data pipelines to feed machine learning models for real-time and large-scale offline use cases.- Support the development of performance dashboards that encompass key metrics to be reviewed with senior leadership and sales management- Work with business owners and partners to build data sets that answer their specific business questions
Required Skills & Experience- 5+ years of data engineering experience- Experience with data modeling, warehousing, and building ETL pipelines- Experience with SQL- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS- Experience mentoring team members on best practices
Preferred Skills- Experience with big data technologies such as Hadoop, Hive, Spark, EMR- Experience operating large data warehouses- Experience with Native AWS services