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Remote mid-level analytics engineer with common SQL/Python/Databricks skills increases candidate competition.
Analytics engineering skills are broadly transferable, though supply-chain experience gives moderate advantage.
Explicit 5+ years plus mandatory Databricks, SQL, Python and BI tooling enforces strict technical screening.
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Build and maintain analytical dashboards and data applications using Databricks Dashboards and Streamlit.
Analyze and transform data with SQL, Python, and Pandas to deliver insights supporting demand forecasting, forecast accuracy, and operational performance.
Collaborate with business stakeholders and Data Engineering teams to translate requirements into actionable metrics and improve data models and reporting capabilities using AI tools.
5+ years of experience in Analytics Engineering, Data Analytics, or Business Intelligence.
Strong hands-on experience with SQL, Python, and Pandas.
Experience working with Databricks and modern data platforms, including building dashboards with BI tools (Power BI, Tableau, Looker, etc.).
Strong communication skills with at least upper-intermediate English proficiency.
Technical analytics professional able to independently build and own analytical products and dashboards.
Experience bridging business and technical teams to convert complex requirements into data-driven insights.
Experience or interest in leveraging AI tools and generative AI applications within analytics workflows.