Analytics Engineer - Data Platform

Aline is building the resident lifecycle platform for senior living: one record that follows every resident from first inquiry through end of life. As part of our Data Platform team, you will build the data foundation behind that vision, giving operators a canonical, reliable record of their residents and communities. This is not just about better dashboards. The models you build become the ground truth that AI agents reason over, the layer that will one day flag a resident at risk, recommend the next best action, and act on it, not just report on it after the fact. You are building the foundation that both humans and agents will rely on to drive better care, retention, and outcomes. What You'll Do Own and extend our dbt models on Snowflake, following medallion architecture (bronze/silver/gold) patterns Manage CDC-based ingestion pipelines (Fivetran and similar tools) landing data from transactional systems into Snowflake Broaden Snowflake and dbt models to become the semantic layer for our reporting and analytics, evolving existing logic out of point tools like Power BI and into a single, governed source of truth Build reliable, well-tested gold-layer datasets that support BI reporting and downstream AI/agentic workloads Apply data modeling best practices (star schemas, SCDs) to support multi-tenant SaaS reporting needs Collaborate cross-functionally with data operations, platform engineering, product teams and others Write dbt tests and documentation so models are trustworthy and self-explanatory for downstream consumers Monitor pipeline health and data freshness, and build alerting so issues surface before they reach a report or dashboard Keep an eye on Snowflake warehouse usage and query performance, and tune models/warehouses as the data volume grows Work directly with stakeholders in Product, Sales, and Customer Success to turn reporting requests into well-modeled data Support row-level security and data access design so multi-tenant customer data stays properly isolated What We're Looking For Strong SQL fundamentals and hands-on Snowflake experience Production experience with dbt; building, testing, and maintaining models at scale Experience with CDC pipelines and ELT tools like Fivetran Familiarity with Power BI, ideally including semantic model / measures work Understanding of medallion architecture and how gold-layer data supports both BI and AI use cases Experience working in a multi-tenant SaaS environment strongly preferred Comfortable with git-based version control and CI/CD for analytics code (dbt/SQL changes reviewed and deployed like software) Working knowledge of an orchestration tool (dbt Cloud, Airflow, Dagster, or similar) for scheduling and monitoring pipelines Python for scripting and automation around data workflows Strong communicator who can translate technical modeling decisions for non-technical stakeholders Comfortable in a lean team environment where you may own a problem end-to-end rather than a narrow slice of it Bonus: exposure to data ontology/semantic modeling for AI/agentic workloads Bonus: familiarity with healthcare data privacy considerations (e.g. HIPAA) given the clinical data our platform touches