Analytics Engineer: dbt, Snowflake & AI Data Pipelines

Bevicareers; Boston (MA); Hybrid; USD 134,000 - 165,000; Full time

Benefits offered by this job

Medical insurance

401(k) matching

Flexible PTO

Parental leave

Job summary

Bevi is hiring an Analytics Engineer to own and optimize data pipelines across finance, operations, IOT, and marketing. You will build ingestions for new sources, maintain dbt models, and design semantic layers used by AI and humans.

This role requires judgment, collaboration, and a proactive approach to data quality and reliability. You’ll work hybrid in Bevi’s data platform, partnering with teams to transform requests into scalable technical solutions and push for robust, well-documented data

Qualifications

• 4–6 years of analytics/engineering experience and a quantitative degree.
• Expertise in dbt and SQL with strong Snowflake knowledge.
• Experience building ingestion pipelines and data platforms.

Responsibilities

• Maintain dbt models and Snowflake layers powering core reports.
• Own marketing data pipeline end-to-end and ingest non-traditional data.
• Diagnose and fix complex data issues to improve resilience.
• Collaborate with cross-functional teams and translate requests.
• Contribute to AI-powered data products and semantic layers.
• Ingest data from Salesforce, NetSuite, Zendesk, and ADP.

Skills

dbt

SQL

Snowflake

Data engineering

Pipeline monitoring

Cross-functional

Data quality

Education

BS in Computer Science

BS in Data Science

Statistics/Engineering

Tools

Salesforce

NetSuite

Zendesk

ADP

Job description

Bevi is hiring an Analytics Engineer to own and optimize data pipelines across finance, operations, IOT, and marketing. You will build ingestions for new sources, maintain dbt models, and design semantic layers used by AI and humans.

This role requires judgment, collaboration, and a proactive approach to data quality and reliability. You’ll work hybrid in Bevi’s data platform, partnering with teams to transform requests into scalable technical solutions and push for robust, well-documented data