Data Engineer I, FAE
Operations Finance Technology team, responsible for building technical solutions for multi-billion WW Operational Cost analytic including Inbound cost (Receiving / PO), variable Cost, fixed cost, outbound (Customer Shipments / Transportation), and Customer Service, is looking for a Data Engineer.
As a data engineer, you will get the exciting opportunity to work on very large data sets in one of the world's largest and most complex data warehouse environments.
You will work closely with the business teams in analysis on various cost savings initiatives, many non-standard and unique business problems and use creative-problem solving to deliver actionable output.
You will be responsible for designing and implementing an analytical environment using third-party and in-house reporting tools, modeling metadata, building reports and dashboards.
You will have an opportunity to work with leading edge technologies like Redshift, Hadoop/Hive/Pig.
You will be writing scalable queries and tuning performance on queries running over billion of rows of data.
Key job responsibilities Design, implement, and support data warehouse / data lake infrastructure using AWS big data stack, Python, Redshift, Quicksight, Glue/lake formation, EMR/Spark/Scala, Athena etc.
Develop and manage ETLs to source data from various commercial, sales and operational systems and create unified data model for analytics and reporting Use business intelligence and visualization software (e.
g.
, Quicksight.
) to develop dashboards those are used by senior leadership.
Empower technical and non-technical, internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.
Develop deep understanding of vast data sources and know exactly how, when, and which data to use to solve particular business problems.
Work with Product Managers, Finance, Service Engineering Teams and Sales Teams on day to day basis to support their new analytics requirements.
Manage numerous requests concurrently and strategically, prioritizing when necessary Partner/collaborate across teams/roles to deliver results.
Mentor other engineers, influence positively team culture, and help grow the team.
A day in the lifeWe believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment.
We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Internal job descriptionLoop competencies--Basic qualifications- 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 practicesPreferred qualifications- Experience with big data technologies such as:
Hadoop, Hive, Spark, EMR- Experience operating large data warehousesWe are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA.
Estimated Salary: $20 to $28 per hour based on qualifications.
As a data engineer, you will get the exciting opportunity to work on very large data sets in one of the world's largest and most complex data warehouse environments.
You will work closely with the business teams in analysis on various cost savings initiatives, many non-standard and unique business problems and use creative-problem solving to deliver actionable output.
You will be responsible for designing and implementing an analytical environment using third-party and in-house reporting tools, modeling metadata, building reports and dashboards.
You will have an opportunity to work with leading edge technologies like Redshift, Hadoop/Hive/Pig.
You will be writing scalable queries and tuning performance on queries running over billion of rows of data.
Key job responsibilities Design, implement, and support data warehouse / data lake infrastructure using AWS big data stack, Python, Redshift, Quicksight, Glue/lake formation, EMR/Spark/Scala, Athena etc.
Develop and manage ETLs to source data from various commercial, sales and operational systems and create unified data model for analytics and reporting Use business intelligence and visualization software (e.
g.
, Quicksight.
) to develop dashboards those are used by senior leadership.
Empower technical and non-technical, internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.
Develop deep understanding of vast data sources and know exactly how, when, and which data to use to solve particular business problems.
Work with Product Managers, Finance, Service Engineering Teams and Sales Teams on day to day basis to support their new analytics requirements.
Manage numerous requests concurrently and strategically, prioritizing when necessary Partner/collaborate across teams/roles to deliver results.
Mentor other engineers, influence positively team culture, and help grow the team.
A day in the lifeWe believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment.
We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Internal job descriptionLoop competencies--Basic qualifications- 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 practicesPreferred qualifications- Experience with big data technologies such as:
Hadoop, Hive, Spark, EMR- Experience operating large data warehousesWe are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA.
Estimated Salary: $20 to $28 per hour based on qualifications.
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