Business Intelligence Engineer, WWGS Retail BI

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

$100K-$160K not verified - source not recorded; timestamp not recorded

401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

16% above the BLS role benchmark for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

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About this role

Business Intelligence Engineer, WWGS Retail BI Seattle, Washington, USA Are you passionate about transforming how Amazon's grocery business uses data to drive customer-obsessed decisions? Join our Retail Business Intelligence team as we revolutionize online grocery analytics and pioneer AI-powered solutions that multiply stakeholder impact. We're seeking an experienced Business Intelligence Engineer to own Online Marketing and Customer Lifecycle analytics-a high-impact role supporting Amazon's ambitious grocery growth goals. You'll be the technical leader enabling data-driven decisions that optimize how millions of customers discover, engage with, and return to Amazon's online grocery offerings. What makes this role exciting: - Strategic impact: Your work directly influences multi-million dollar marketing investments and customer acquisition strategies across Online and Sub Same Day (SSD)-Grocery, supporting an S-Team goal to grow active perishables customers - AI innovation opportunity: Build and deploy business-facing AI solutions that transform how grocery stakeholders interact with data-from automated insights generation to self-service analytics agents that answer complex questions in minutes instead of days - Complex problem-solving: Build analytics solutions for ambiguous challenges like marketing attribution, customer funnel optimization, and lifecycle segmentation where measurement standards don't yet exist - Cross-functional influence: Partner with Marketing, Product, Tech, and Data teams across organizations to establish unified measurement frameworks and drive alignment on strategic initiatives - Technical breadth: Design scalable ETL pipelines, build multi-touch attribution models, create automated reporting infrastructure, implement experimentation frameworks, and develop AI agents using AWS technologies (Bedrock, Redshift, Athena, QuickSight, S3) You'll tackle challenges like: - Reducing customer ingress attribution gaps from

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