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Popular mid-level analytics title, broad technical BI/SQL requirements, and likely metro hiring drive high candidate competition.
Role requires specific analytics stack and semantic modelling, making background moderately transferable across industries.
Explicit 5–8 years and required Redshift/AWS/BI expertise impose strict technical filters.
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Design and own enterprise-grade semantic data models and standardize KPIs across business units.
Collaborate with Data Engineers and BI teams to build, optimize, and support scalable BI solutions and dashboards using AWS QuickSight, Tableau, and Power BI.
Lead data governance, performance tuning (SQL on Redshift-like MPP systems), advanced data security (RLS/CLS), and mentor junior engineers.
5 to 8 years overall analytics experience with strong analytics engineering skills.
Proficient in advanced SQL (Redshift or similar MPP) and AWS data ecosystem including Redshift and DynamoDB.
Experience with BI visualization tools like QuickSight, Tableau, or Power BI.
Bachelor's degree in Computer Science, Engineering, or related field.
Experienced in bridging data engineering and business analytics to deliver scalable BI platforms and semantic layers.
Strong hands-on expertise in data modeling, complex SQL performance optimization, and implementing data governance/security best practices.
Capable of mentoring junior engineers and collaborating effectively across distributed teams in a global organization.