We are building a world‐class data platform that powers decision‐making across the business—from product and marketing to finance and executive leadership.
As a Senior Data Engineer, you will be a high‐impact individual contributor working across a modern data stack, including Snowflake, dbt, and ELT pipelines.This is a high‐autonomy role for someone who cares deeply about data quality, reliability, and scalability.
You will design and operate robust data systems, translate business needs into technical solutions, and help establish best‐in‐class data engineering practices.
If you enjoy building fast, trustworthy, and maintainable data platforms at scale, this role is for you.ResponsibilitiesArchitect and optimize the Snowflake data platform, including warehouse sizing, cost optimization, storage strategy, and access controlsDesign and own dbt project structure, including models, macros, testing, documentation, and scalable data contractsBuild and maintain ELT pipelines using Fivetran and orchestration tools, ensuring reliable data ingestion across multiple sourcesImplement and manage data quality and observability frameworks (tests, SLAs, lineage, monitoring, incident response)Translate business requirements into scalable data models and reusable datasetsPartner with Analytics, Product, and Marketing teams to deliver high‐quality, self‐service data solutionsEstablish and enforce data modeling standards (dimensional and ER models)Optimize query performance and warehouse costs in Snowflake, providing insights to stakeholdersDefine and enforce data governance policies, including RBAC, masking, and PII handlingOwn end‐to‐end delivery of complex data initiatives, from design to productionQualifications5+ years of experience in data engineering building and operating production data pipelinesDeep expertise with Snowflake (architecture, cost optimization, governance, RBAC, masking)Strong experience with dbt (modeling, testing, macros, project structure)Strong knowledge of data modeling (dimensional and entity‐relationship)Experience designing and maintaining scalable, production‐grade data pipelinesBachelor's degree in Computer Science, Data Engineering, or equivalent experienceProficient in Snowflake, SQL, data modeling (dimensional & ER)Experience with orchestration tools (Airflow, Prefect, Dagster)Familiarity with data observability tools (Monte Carlo, Atlan, dbt Explorer)Experience with event streaming systems (Kafka, Kinesis)BenefitsWork remotely Monday‐Friday, 40 hours a week (no weekends)Quarterly Home Office ReimbursementPayroll Deduction Purchase PlansAccess to Training and Professional Development Platforms
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