Data Engineer

Snowflake

• account admin, role and security configuration, performance and cost management alongside data leadership

Sigma semantic layer

• build and maintain the governed datasets (joins, transpositions, derived metrics) that power AdOps, Sales, Finance, and Executive reporting and Sigma's native AI agents

dbt models

• spec what's needed, scope with Datateer (who builds and runs them), review their work, keep the warehouse catalog current

Fivetran (in-house)

• operate Salesforce, HubSpot, and other ingestion that lives with us
• reverse-ETL into Salesforce, HubSpot, NetSuite: especially flows where the decision logic lives in Sigma
• partner with the named owner of each destination before any write goes out

Sigma access governance

• keep dataset curation tight; approve explore- and build-access changes alongside data leadership

Dashboards

• internal and customer-facing views, with attention to reliability, performance, and clarity for non-technical users

Convey + Sigma agents

• help shape where each tool lives in the stack, and design the Sigma Actions / Convey integration seam

End-of-month and financial-adjacent analytics

• delivery-in-full and pacing frameworks, sales order vs. invoice reconciliation, media cost validation
• build repeatable processes that reduce manual work
• data quality SLAs for AdOps, billing, and Salesforce datasets; detect, prevent, and remediate at the source

Analysis and experiments

• patterns in campaign performance, pricing, margin, and throughput
• bidding, pacing, and audience tests with appropriate sizing and structure
• recommendations to operating leaders

Automation, documentation, reproducible workflows

• de-risk month-end and seasonal processes

Qualifications

• Expert SQL and data warehousing: schema design, performance tuning, modeling for analytics workloads
• Cloud data platforms: hands-on, ideally Snowflake (cost / performance, role-based security, workload management)
• Modern ELT / data engineering tooling: Fivetran or similar; dbt or dbt-style modeling; reverse-ETL (Census, Hightouch, Fivetran Activations)
• BI / data visualization: ideally Sigma; governed datasets, internal and customer-facing dashboards, narratives for business users
• Salesforce + cross-system integration: GTM, revenue, and delivery datasets across Salesforce, ERP / invoicing, and DSP / platform data
• Cloud-warehouse APIs: designing or consuming APIs for third-party platform integration
• Working with managed data partners: scoping vendor / consultant work, reviewing output, holding the relationship to outcomes
• Working alongside AI tooling: BI-native AI agents (Sigma) and cross-system automation (Convey), with a point of view on where each belongs
• Programming: Python, R, Go, or similar for data processing, modeling, and automation
• Analytical and statistical foundation: predictive modeling basics, A/B and multivariate experimental design, measurement and KPI design
• Translating complex data into simple, actionable outputs for non-technical stakeholders
• AdTech / programmatic experience (CTV, open web, DSPs such as The Trade Desk) a strong plus

Education

• BS or MS (preferred) in CS, Data Science, Statistics, Math, or related quantitative field; or equivalent professional experience

Experience

• 7+ Years experience in a data engineering or BI role, in a senior IC or lead capacity

Compensation

The base salary range for this position is $111,000–$130,000 annually, plus bonus eligibility and comprehensive benefits; actual compensation will be based on the candidate’s skills, experience, and qualifications.