Analytics Engineer

Remote (US East Coast / Eastern Time Zone Preferred), Eastern Time Zone preferredFull-TimeMiddle

SalarySalary Min: $120,000 Salary Max: $160,000. This role is also eligible for Convene's annual incentive performance bonus plan.

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Job Details

Experience: 3+ years in analytics engineering, data engineering, or BI development
Required Skills: SQLSnowflakeData modelingdbt

Have 3+ years of experience in analytics engineering, data engineering, or BI development, building data products people rely on.
Write strong SQL.
Have built and maintained dbt models in production.
Have worked with a cloud data warehouse; Snowflake is preferred.
Have experience with ELT ingestion tools such as Fivetran and troubleshooting schema changes, late-arriving data, and API limits.
Understand dimensional modeling, medallion layering, grain, slowly changing dimensions, and event lifecycles.
Have built dashboards or self-service data products used for decision-making.
Test and document work as a regular practice.
Use AI agents for multi-step tasks such as writing SQL and dbt models, generating tests, and drafting documentation, and verify their output.
Explain work clearly to technical and non-technical partners.

Partner with Finance, Sales, Operations, and venue teams to translate business needs into trusted models and metrics.
Set up and maintain Fivetran connectors, land data in bronze, and troubleshoot schema drift and load failures.
Build dbt models through bronze, silver, and gold layers, shaping gold models around how the business operates.
Define and maintain semantic-layer metrics, dimensions, relationships, synonyms, and descriptions.
Build ThoughtSpot models and Liveboards that support self-service data exploration.
Create and maintain golden question sets and regression tests for conversational analytics, blocking releases that fail.
Apply data governance practices, including sensitive-data tagging, tag-based masking, and row access policies.
Monitor freshness, data quality, and pipeline health; tune models, queries, and warehouse sizing.
Use AI agents for end-to-end data work and review agent-produced code to the same standard as teammate code.

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