Note: The job is a remote job and is open to candidates in USA. Strategus is a CTV‑first managed service partner specializing in programmatic Connected TV advertising. As a Senior Data Engineer, you will manage the Snowflake data warehouse and collaborate with various stakeholders to ensure data integrity and performance while delivering insightful analytics.
Responsibilities
- 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
- Datateer service requests: triage, prioritize, sign off on scope, escalate when blocked
- 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 to de-risk month-end and seasonal processes
Skills
- 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
- 7+ Years experience in a data engineering or BI role, in a senior IC or lead capacity
- 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
Benefits
- Bonus eligibility
- Comprehensive benefits
Company Overview