Sr. Analytics Engineer
New
B
BackblazeCloud Data/Analytics
Remote - US, Maintain meaningful working-hours overlap with US Pacific time zone teamsFull-TimeSenior
Salary160,000 - 185,000 USD per year
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Job Details
- Languages
- English
- Experience
- 8+ years of experience
- Required Skills
- SQLGitSnowflakeData engineeringCI/CDData modelingdbt
Requirements
- 8+ years of experience in analytics engineering, data engineering, business intelligence, or a closely related role.
- Advanced SQL proficiency with proven experience building production-grade, well-tested analytical data models.
- Strong hands-on dbt experience, including modeling from staging to marts, macros, documentation, and CI/CD.
- Hands-on experience building and running dbt on a modern cloud data warehouse (Snowflake strongly preferred).
- Experience building or operating a semantic or metric layer (e.g., dbt Semantic Layer, MetricFlow, Cube, or LookML).
- Experience applying software engineering principles including Git-based version control, code review, and automated testing.
- Solid grounding in data modeling (dimensional/domain-driven) and defining logic from ambiguous requirements.
- Excellent written and verbal communication skills in English.
- Ability to work effectively with both technical and non-technical stakeholders.
- Must be able to maintain meaningful working-hours overlap with US Pacific time zone teams.
Responsibilities
- Design, build, and maintain dbt models from staging through marts using software engineering best practices like version control, code review, and CI/CD.
- Stand up the semantic layer and define certified, single-source-of-truth business metrics such as ARR, MRR, and customer retention.
- Migrate complex business logic from BI tools and manual SQL into governed, reusable, version-controlled models.
- Build a repeatable pipeline for shipping certified data products with defined schemas, lineage, and auditability.
- Implement automated testing and observability to ensure data quality and trust.
- Partner with Finance, Revenue Operations, and Marketing to align on metric definitions and support financial-reporting-relevant revenue models.
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