About the role Lifetime Brands is looking for a BI Analytics Engineer to build the data products our business runs on — and to make sure people actually use them. You own reporting end to end: the pipelines that move the data, the models that shape it, and the dashboards that put it in front of decision-makers. Our data team supports 500+ users and 150+ production reports on a modern stack — Airbyte for ingestion, Snowflake as the warehouse, dbt Core for transformation, and Qlik Sense for reporting across both client- managed and Qlik Cloud. You don't need to have used every piece of it. You need to have done this kind of work somewhere, and be able to pick up the rest. The immediate focus is a major retail reporting buildout — POS and sell-through, replenishment, inventory, and on-shelf availability for one of our largest accounts — alongside a longer-running migration of legacy reporting onto dbt and Snowflake. a growing program with real room to shape how it gets built. What you will do

• Partner with business stakeholders to turn open-ended questions into clear reporting requirements and meaningful KPIs.
• Design and build Qlik Sense apps — load scripts, set analysis, master items — that are governed, documented, and trustworthy enough for people to use on their own.
• Develop, test, and document transformation models in dbt Core on Snowflake, following dimensional modeling best practices.
• Build and maintain ingestion pipelines into Snowflake with Airbyte, including incremental and CDC patterns from sources such as MSSQL/Azure SQL and SAP.
• Maintain and extend our code-based pipelines — Python scripts orchestrated through scheduled GitHub Actions workflows.
• Own data quality, monitoring, and reliability for everything you build, and help hold that standard across the wider reporting estate.
• Act as a bridge between the BI team and the rest of the business on data sources, data access, and what's available to report on.
• Teach. Show non-technical teams how to use what you've built, and bring new tools and practices back to the BI team.
• Maintain documentation for the systems, processes, and decisions behind your work.
• Work in Git and follow our code review and CI/CD practices. What we are looking for
• 4+ years in BI engineering, analytics engineering, or data engineering — with genuine ownership of reporting, not pipelines alone.
• Expert SQL and a strong grasp of dimensional and data modeling.
• Production experience transforming data in a cloud warehouse. dbt on Snowflake is our stack; close equivalents count.
• You've built and owned dashboards a real business audience relied on. Qlik Sense experience is a significant advantage.
• Comfortable working independently and end to end, from source system to finished report.
• Excellent verbal and written communication — you can explain a complex data problem to someone who doesn't work in data.
• Careful, methodical troubleshooting and close attention to detail.
• Bachelor's degree in a STEM field, or equivalent practical experience. Nice to have
• Deep Qlik Sense expertise: load scripting, set analysis, security rules, and QMC administration across on-prem and Qlik Cloud.
• Retail or CPG background — retailer data portals, syndicated and POS data sources (Circana, NielsenIQ), and EDI workflows.
• Familiarity with SAP data: ECC table structures, BW InfoProviders, and IDoc/EDI extraction.
• Strong Python for pipeline development, automation, and API integrations.
• Experience with a modern ELT tool such as Airbyte, Fivetran, or Stitch, including CDC-based replication.
• Experience supporting a large, multi-tenant reporting environment.

Your first 90 days You'll have ramped on our stack and shipped your first reporting deliverable end to end — source system to dashboard — tested and documented well enough that the rest of the team can build on it