Data Engineer

Data EngineerMid-Level | Full-Time | On-Site | Reports to Director of FP&APosition SummaryThe Data Engineer is a mid-level individual contributor responsible for the systems and structures that make the company's data reliable, accessible, and useful. This role owns the design and operation of the ingestion pipelines, transformation logic, and data models that serve both business intelligence and AI initiatives.This isn't a role that waits for fully formed requirements. You'll be expected to understand how the business operates and apply that knowledge to technical decisions. A pipeline that runs on time but models the business incorrectly hasn't done its job.What You'll DoData Ingestion & OrchestrationDesign, build, and maintain ingestion pipelines from source systems into SnowflakeOrchestrate workflows in Dagster so they're observable, reliable, and operationally soundMonitor pipeline health and data availability; investigate failures, fix root causes, and add alerting so issues surface earlyTransformation & ModelingDevelop and maintain dbt models that turn raw data into clean, tested, well-documented datasetsDesign dimensional models and data marts that support both reporting and machine learningImplement data quality checks and testing standards so downstream consumers can trust datasets without re-verifying themAI Data PreparationStructure feature datasets and training data pipelinesPartner with data science and AI teams on data quality, freshness, and structure requirementsContribute to the semantic layer that gives analytics and AI consumers consistent access to business metrics and entitiesKeep data lineage and governance in viewBusiness PartnershipBuild working knowledge of core business processes: product sales through dealership partners, claims administration, and cancellationsEngage directly with business stakeholders to understand data needs and translate them into sound technical designsApply business context to modeling decisions, pipeline priorities, and data quality standardsPlatform DirectionAdvise on the strategic direction of the data engineering toolset, including platform updates and new capabilitiesStay current on best practices in data engineering, AI data preparation, and orchestrationAdjacent WorkDashboards and reporting belong to analysts and BI developers, but you may occasionally build or troubleshoot a report, or help an analyst work through a modeling issue at the source.What You BringRequired3–7 years of experience in data engineering or a closely related disciplineStrong SQL proficiencyHands-on experience with a cloud data warehouse, a transformation/modeling framework, and a workflow orchestration toolAbility to work with non-technical stakeholders and translate business needs into technical requirementsClear written and verbal communication, including documentation others can use without a follow-up conversationStrongly PreferredSnowflake, dbt, and DagsterAWS familiarity (storage, IAM, basic networking)Nice to HavePython for pipeline development or scriptingData quality frameworks, data contracts, or observability toolingExperience supporting ML pipelines or AI data preparationMedallion or similar layered architectureData governance or data catalog experienceTech Environment: Snowflake, Dagster, dbt, AWS (S3, EC2, IAM), Python, GitHubWorking ConditionsOn site at corporate headquarters, collaborating in person with technology and business teams. Not remote. Minimal travel.