Applied Data Engineer

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