Sr Data Engineer

Senior Data Engineer  Data & Analytics  About the Role  We are hiring a Senior Data Engineer to shape and strengthen the data foundation that drives company performance.  This is a senior individual contributor role with meaningful influence. You will define engineering standards, evolve our data platform, and ensure data is reliably integrated and structured to support confident decision making across the organization.  Success in this role requires more than technical execution. You will be expected to operate independently, bring structure to ambiguity, challenge unclear assumptions, and translate complex system and business problems into durable data solutions.  Key Responsibilities  Data Platform Leadership  Lead the development and continuous improvement of data pipelines and integration frameworks  Define standards for ingestion, orchestration, and data movement across the platform  Improve reliability, performance, and cost efficiency of data pipelines and storage  Design scalable, reusable patterns that support consistent data flow across systems  Data Integration and Architecture  Design and implement integrations across internal and external systems using tools such as Fivetran and custom pipelines  Own how data enters and moves through the warehouse, ensuring consistency and integrity  Structure data layers to support both upstream flexibility and downstream consumption  Ensure strong alignment between source system logic and warehouse representations  Data Modeling and Foundation  Architect and implement core data models in Snowflake using dbt  Build durable data layers aligned to core revenue and operational domains  Ensure strong alignment between upstream data structures and downstream reporting needs  Embed testing, documentation, and performance optimization into standard engineering practice  Data Reliability and Quality  Establish and enforce data quality standards across ingestion and transformation layers  Design systems for validation, monitoring, and lineage  Proactively identify and resolve data issues, reducing ambiguity and downstream impact  Strengthen trust in enterprise data through consistent and reliable delivery  AI-Enabled Data Systems  Treat AI as a core capability in modern data engineering, leveraging it to deliver high-quality solutions with greater speed and rigor  Design data pipelines and structures that enable safe and effective use of AI with trusted data  Integrate AI into engineering workflows to accelerate development, monitoring, and optimization  Apply disciplined judgment when evaluating AI-generated outputs, ensuring enterprise standards for accuracy and consistency  Establish practical guardrails for responsible AI usage across both engineering and business consumption  Cross-Functional Partnership  Translate complex and ambiguous business questions into scalable data solutions  Communicate technical tradeoffs clearly to both…