Senior Data Analytics Engineer

• Architect and stand up a Snowflake environment, including account setup, databases and schemas, virtual warehouse strategy, RBAC, security, data governance, cost controls, and monitoring.
• Design and implement reliable ELT pipelines from Salesforce, Gong, Spiff, Clay, Common Room, and internal product data sources using connectors, APIs, and Snowflake-native capabilities (Snowpipe, Streams, Tasks).
• Ingest and normalize semi-structured data (JSON/VARIANT), implement CDC, and build resilient orchestration with tools such as Airflow, Prefect, Dagster, or cloud-native schedulers.
• Model data for analytics using best practices (dimensional modeling/Kimball, data marts, medallion architecture) to create trusted, documented datasets for GTM, Product, and Finance use cases.
• Own dbt-based transformations, testing, and CI/CD, including version control, code reviews, and deployment workflows.
• Establish data quality, reliability, and lineage standards with automated tests, monitoring, alerting, and SLAs; create runbooks and documentation.
• Build and optimize BI assets in Power BI or Tableau, including semantic models, governed metrics, executive-ready dashboards, and query performance optimization against Snowflake.
• Partner with stakeholders to define and operationalize key metrics (pipeline, conversion, ARR, retention, product adoption), and regularly present findings and recommendations to leadership.
• Implement and maintain security and compliance controls (PII handling, data masking, role-based access, auditing, retention).
• Monitor and tune performance and cost (warehouse sizing, caching, micro-partitioning, clustering, materialized views); drive continuous improvement in reliability and efficiency.
• Evaluate and integrate new tools and vendors; contribute to data platform roadmap and best practices.

• 5+ years of data engineering experience, with 3+ years hands-on in Snowflake and a track record of building a Snowflake environment from scratch.
• Deep expertise with Snowflake features: virtual warehouses, RBAC, security policies, Time Travel, zero-copy cloning, Snowpipe, Streams, Tasks, materialized views, and performance tuning.
• Proven experience building pipelines from Salesforce, Gong, Spiff, Clay, and Common Room, plus internal product usage telemetry (e.g., events, logs). Comfortable with third-party connectors (e.g., Fivetran/Stitch), APIs/webhooks, and Python-based ingestion.
• Strong SQL and Python; experience with dbt for transformation and testing, Git-based workflows, and CI/CD.
• Advanced data modeling skills (dimensional modeling/Kimball), data warehousing concepts, and building semantic layers for BI.
• Extensive experience with Power BI or Tableau, including data modeling (e.g., DAX or Tableau calculations), dashboard design, and performance optimization with Snowflake as the backend.
• Excellent communication skills and comfort presenting to senior leadership; ability to translate technical details into business value and actionable insights.
• Experience in a major cloud (AWS, Azure, or GCP) including IAM/SSO, networking, secrets management, and logging/monitoring.
• Strong focus on data quality, documentation, and operational excellence.

• Experience with RevOps data, CRM schemas, Gong audio/transcript metadata, compensation/commission data (Spiff), lead enrichment (Clay), and community/product signals (Common Room).
• Familiarity with product analytics tools and event pipelines (Segment, Snowplow, Amplitude) and modeling product usage and adoption metrics.
• SnowPro Core/Advanced Architect certification or equivalent cloud certifications.
• Experience with metric layer tooling, data contracts, and governance frameworks.

• Stand up a secure, cost-aware Snowflake environment with production, staging, and development tiers, RBAC, and monitoring.
• Deliver initial ELT pipelines for Salesforce and at least one additional source (Gong, Spiff, Clay, or Common Room), plus an MVP product usage ingestion.
• Ship an executive-ready dashboard in Power BI or Tableau with a governed metric set and documented data lineage.
• Implement dbt transformations and data tests for core domains; establish CI/CD and operational runbooks.

• Flexible; remote-friendly with overlap to core business hours.
• Occasional travel for team onsites or leadership presentations may be required.

BlueVoyant Candidate Privacy Notice

To understand how we secure and manage your personal data upon submitting a job application, please see our Candidate Privacy Notice, which can be found here - Candidate Privacy Notice