Senior Data Analytics Engineer building automated reporting and business insights for Dotmatics’ cloud scientific research platform. Partnering across Sales, Product, Marketing, and Finance to enable self - service analytics.
About the role
- Senior Analytics Engineer building trusted, AI-ready analytics infrastructure for Luxury Presence’s real estate growth platform. Owning dbt, Snowflake, Python pipelines, semantic layers, and cross-system data quality.
Responsibilities
- Build and own the dbt project, ensuring models are performant, well-tested, and documented
- Design and maintain the Snowflake data warehouse and ingestion processes
- Create core entities and datasets using modern data modeling best practices
- Build and maintain custom Python/Airflow pipelines for third-party API ingestion into Snowflake
- Design and operate cross-system reconciliation models to surface discrepancies and protect revenue
- Implement testing and observability for analytics pipelines
- Enforce CI/CD practices including automation, linting, tests, code review, and approvals
- Standardize metric definitions across tools
- Investigate and document data incidents from root-cause analysis through remediation and stakeholder communication
- Act as data liaison between Engineering, GTM, and Finance
- Enable stakeholder self-service access to trusted insights and promote data literacy
- Design and maintain Snowflake Cortex semantic views for AI agents and LLM-powered tools
- Partner with AI/product teams on semantic-layer definitions for internal AI assistants
- Build measurement frameworks for AI initiatives, including experiment design and attribution modeling
- Establish trusted analytics layers, improve data quality and reliability, reduce time-to-insight, quantify discrepancies, and define success metrics for new initiatives
Requirements
- 5+ years of experience as an analytics engineer, data engineer, or similar role in a SaaS environment
- Deep expertise in SQL, dbt, and modern data modeling best practices
- Proficiency in Python for pipeline development, API integrations, and automation
- Experience modeling Salesforce opportunities, contracts, subscriptions, cases, and field history data
- Experience building custom ELT pipelines from third-party APIs into a cloud data warehouse
- Experience designing cross-system reconciliation models across multiple source systems
- Experience with event-based and product usage data such as PostHog or Mixpanel
- Experience connecting paid advertising, campaign, and attribution data to product analytics
- Experience designing and maintaining governed semantic layers such as dbt Semantic Layer or Snowflake Cortex
- Comfort with large-scale data systems including Snowflake, BigQuery, or Redshift
- Familiarity with CI/CD, Git-based workflows, and automated testing
- Experience collaborating with engineers, analysts, and product managers
- Demonstrated success using analytics to drive decisions in technical or product-focused environments
- Comfort taking ownership of ambiguous problems and designing end-to-end solutions
- Nice to have: Airflow DAGs, statistics and experiment design, predictive modeling, financial SaaS metrics and billing operations, and people analytics
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