Analytics Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• 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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Salary

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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

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.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

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

State eligibility is not yet verified.

About this role

Analytics Engineer TLV Bringg is the infrastructure behind delivery operations for some of the world's largest retailers. Every year, we process over 200 million orders through our smart, automated omnichannel platform experience. When it works, deliveries land on time. When it doesn't, customers feel it fast - and so do we. We are looking for an Analytics Engineer to maximize the potential of our data ecosystem and drive its future growth. On a day-to-day basis, you will leverage our fully established Medallion Data Architecture in Google BigQuery, using SQL, Python, and dbt to implement new data solutions, support upcoming strategic initiatives, and maintain robust data models. By managing our unified semantic layer and treating data as code, you will ensure a single source of truth that directly fuels Bringg's advanced analytics, machine learning projects, and GenAI operations. In this role, you will: - Leverage & Scale the Medallion Pipeline: Own, optimize, and extend our production-ready dbt data models across Bronze, Silver, and Gold layers in Google BigQuery to support new business use cases. - Ensure Data Quality & Governance: Implement and enforce robust dbt data tests to surface inconsistencies early, define model health scores, and maintain comprehensive column-level documentation. - Own the Semantic Layer: Maintain and scale our unified dbt Semantic Layer, guaranteeing a single source of truth for business metrics utilized by internal business operations, customer-facing embedded analytics, and AI/ML initiatives. - Bridge Engineering and Impact: Collaborate closely with Data Engineers, Data Scientists, and BizOps teams to ingest new

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