Senior Analytics Engineer – US

About This Opportunity

We are representing a fast-growing Series C SaaS platform in the proptech space. Our client has scaled to significant ARR and serves tens of thousands of users nationwide. They are seeking a Senior Analytics Engineer to build and own the analytical foundation that drives decision-making across Go-to-Market, Product, Finance, People, and Operations teams.

This role sits at the intersection of data engineering and analytics. You will transform raw product, marketing, financial, and operational data into clean, well-modeled datasets that power executive dashboards, cohort analyses, experimentation, billing operations, and AI-enabled semantic layers. This is a highly cross-functional position requiring partnership with Product, Marketing, RevOps, Finance, People Ops, and Engineering leadership.

Responsibilities

• Own and evolve the dbt project, ensuring models are performant, well-tested, and documented
• Design and maintain the Snowflake data warehouse and data ingestion processes
• Apply modern data modeling best practices to create core entities and datasets that reflect complex business logic
• Build and maintain custom Python/Airflow pipelines to ingest data from third-party APIs into Snowflake
• Design cross-system reconciliation models that compare data across source systems to surface discrepancies and protect revenue
• Implement testing, observability, and CI/CD best practices for analytics pipelines
• Standardize metric definitions and ensure consistency across tools and dashboards
• Investigate and document data incidents from root cause through remediation and stakeholder communication
• Act as data liaison between Engineering, GTM, and Finance to ensure consistent metric definitions and proper instrumentation
• Enable stakeholder self-service access to trusted insights and drive data literacy across the organization
• Design and maintain Snowflake Cortex semantic views to serve as governed data interfaces for AI agents and LLM-powered tools
• Partner with AI and product teams to build and validate semantic layer definitions
• Build measurement frameworks for AI-powered initiatives, including experiment design and attribution modeling

What We're Looking For

Must Have:

• 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 data (opportunities, contracts, subscriptions, cases, field history)
• Proven experience building custom ELT pipelines that ingest data from third-party APIs into cloud data warehouses
• Experience designing cross-system reconciliation models to surface data discrepancies
• Proven experience working with event-based and product usage data (e.g., Posthog, Mixpanel)
• Experience connecting marketing data (paid ads, campaigns, attribution) to product analytics and building end-to-end pipelines from ad platforms through conversion and retention metrics
• Experience designing and maintaining semantic layers (dbt Semantic Layer, Snowflake Cortex, or similar)
• Comfortable with large-scale data systems (Snowflake, BigQuery, Redshift)
• Strong familiarity with CI/CD, Git-based workflows, and automated testing
• Experience collaborating cross-functionally 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:

• Experience building and maintaining Airflow DAGs and orchestrating multi-source API ingestion pipelines
• Strong foundation in statistics and experiment design (A/B testing, significance testing, incremental impact measurement)
• Experience with predictive modeling fundamentals (classification, feature selection, model evaluation)
• Familiarity with financial SaaS metrics and billing operations (ARR/MRR/NRR, subscription reconciliation, revenue recognition)
• Experience with people analytics (headcount, attrition, compensation benchmarking)

How We Work With You

Get A Job.ai specializes in placing exceptional analytics and data talent with innovative technology companies. When you apply through our platform, a member of our recruiting team will review your profile and conduct an initial screen. If there's a strong match, we will submit your candidacy to our client and guide you through their interview process.

Please apply exclusively through Get A Job.ai. Do not attempt to contact the client directly, as all applications must come through our official channel to be considered.

Pay

Compensation details will be discussed during the screening process with our talent team.

Equal Opportunity: Get A Job.ai is committed to inclusive hiring practices. We welcome applicants of all backgrounds and work with clients who share our commitment to building diverse, equitable teams.