Description

Scentsy is looking for an Applied Data Engineer to provide innovative modernization and ensure the availability, reliability, and performance of Scentsy’s Data Analytics eco-system.

Note: Our company is unable to provide visa work sponsorship for this position.

This job is worked on-site at our headquarters in Meridian, ID.

What You Will Do:

• Assembling large, complex sets of data that meet non-functional and functional business requirements
• Identifying, designing, and implementing internal process improvements, including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes 
• Building required infrastructure for optimal extraction, transformation, and loading of data from various data sources using AWS and SQL technologies
• Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics, including operational efficiency and customer acquisition 
• Working with stakeholders including the Executive, Product, Data, and Design teams to support their data infrastructure needs while assisting with data-related technical issues
• Working with the architects, including enterprise, application, and data architects, to design, implement, and support Scentsy’s data lake
• Translating analytical program models, including but not limited to scripting, error handling, and documentation 
• Evaluating new technologies for data and technology modernization within Scentsy’s data ecosystem
• Acting as technical lead for data lead projects and initiatives
• Coaching and mentoring to less experienced engineers
• Performing all other assigned tasks and requirements as needed

We're Looking For:

• Graduate and/or bachelor’s degree in Information Systems, Informatics, Statistics, Computer Science or another quantitative field
• 5 years of data engineering experience 
• Ability to build and optimize data sets, data pipelines and architectures 
• Ability to perform root cause analysis on external and internal processes and data to identify opportunities for improvement and answer questions 
• Excellent analytical skills associated with working on unstructured datasets 
• Ability to build processes that support data transformation, workload management, data structures, dependency and metadata
• Recommends data strategies, ETL processes, and procedures for getting data in and out of the data lake
• Experience in data access and delivery technologies, including familiarity with data quality assessment, data organization, metadata, and data profiling
• Ability to take complex, ambiguous problems, break them down into smaller parts, and problem solve to come up with a whole, integrated, and strategic solution
• Demonstrated understanding and experience using software and tools including relational NoSQL and SQL databases including SQL Server and Postgres
• Hands on experience with AWS Services like Cloud Formation, S3, Glue, Lambda, Event Bridge, SNS/SQS, and others
• Demonstrated ability to self-learn and lead teams into new technologies and engineering methods
• Demonstrated ability to solve technical problems relevant to data engineering using programming languages (SQL and Python)
• Demonstrated ability to solution with AWS services and provision infrastructure from code/template
• Excellent data manipulation and analysis skills
• Excellent skills in SQL, data modeling, data warehousing, data lake, and OLAP
• Excellent written and oral communication skills
• Experience with Bitbucket and TeamCity, a plus
• Experience with Redgate Flyway, a plus
• Familiarity with Agile Framework