Bachelor's degree in a data-related field or equivalent experience
5 years in data warehouse engineering or 3 years in Business Intelligence
Knowledge of best practices in data modeling and ingestion
Experience with cloud data warehousing tools like Snowflake and RedShift
Proficiency in BI tools such as AWS QuickSight and Power BI
Strong SQL skills and experience in data warehousing and OLAP
Excellent analytical and problem-solving abilities
Responsibilities
Provide data analytics capabilities for internal business partners
Design and implement reports and dashboards as technical lead
Develop and maintain data warehouse infrastructure
Collaborate with team on data warehouse operational issues
Define data requirements in coordination with data analysts
Build data models to support business analytics
Design, develop, and deploy data pipelines and automation solutions
Benefits
Supportive work culture fostering collaboration and mentorship
Opportunities for skill enhancement through training
Challenging projects in a growth-oriented environment
Access to advanced data technologies and tools
Engagement with a variety of business functions across the company
Full Job Description
Data Engineer
This job is worked 100% of the time in-office at our Meridian, ID corporate office.
*Please note: We are unable to provide H-1B visa work sponsorship for this position.
What You'll Do:
Serve as part of our Data Engineering and Analytics team providing data analytics capabilities for various internal Scentsy business partners
Influence and evangelize analytical methodologies to support business partners' needs
Act as a technical lead for designing and implementing custom reports and dashboards
Assess requirements and assist with developing data warehouse infrastructure
Confer with the immediate team on warehouse operational issues and recommend resolutions
Interface with data analysts to define and implement data requirements to meet their analytic needs
Participate in the design and build of conceptual, logical, and physical data models to support business analytics from the data warehouse
Recommend data strategies, ETL processes, and procedures for getting data in and out of the data warehouse
Design, develop, and deploy data pipelines, integrations, and automation solutions, applying sound software engineering practices across the development lifecycle
Test reporting solutions and provide training
Interact with technical resources from various teams within the Information Systems and Information Technology departments to define and test technical changes to the system
Design and implement custom reports and dashboards
Translate analytical program models, including but not limited to scripting, error handling, and documentation
Work with users from various functional areas (sales, order processing, shipping, logistics, credit, finance, marketing, etc.)
Analyze processes ensuring sustainability, supportability, and automation
Identify new data from additional internal or 3rd party systems and transform it to work cohesively within existing Data Warehousing models
Participate in evaluating new technologies to ensure data and technology architecture advancement within the organization's BI needs
Identify development needs to improve and streamline business operations
Provide stakeholders with quality data so the business can make sound, data-driven decisions and recommendations
Coach and mentor less experienced engineers
Perform all other assigned tasks and requirements as needed
We're Looking For:
Bachelor's degree in business, Business Intelligence, Data Warehouse or data related field or equivalent related experience
5 years of data warehouse engineering experience and/or 3 years of Business Intelligence experience
Significant knowledge of best practices for data modeling, dimensional modeling (Star schema), data ingestion, queries, and data loading options
Wide experience of cloud data warehousing tools and technologies such as Snowflake and RedShift
Significant experience with BI tools such as AWS QuickSight, Power BI, R, Python, SAP Business Objects and Web Intelligence (WEBI) reporting tools
Experience with AWS Services like AWS Quick, Cloud Formation, S3, Glue, State Machine, Lambda, Event Bridge, SNS and Appflow.
Excellent data manipulation and analysis skills
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
Excellent skills in SQL, data modeling, data warehousing, and OLAP
Strong solution development capabilities, including the ability to design, build, test, and deploy production-quality code and automation
Excellent written and oral communication skills
Experience with SAP systems including table structure, field definitions, CDS views and usage, a plus
Experience with git
Advanced critical thinking, problem solving, and analytical skills
