Staff Data Engineer

About the role

Join our team as a Staff Data Engineer, where you will provide senior technical leadership for our data engineering team. You will own a defined slice of our centralized Databricks data platform, drive architectural judgment, and serve as the onshore escalation point for platform decisions. This hands-on role focuses on building and maintaining production pipelines, exercising architectural judgment on data modeling and pipeline design, and engaging with product and engineering stakeholders. You will also drive platform quality, serve as a knowledge backup for platform decisions, and implement data pipelines that serve multiple product lines. Key missions: Assumer la responsabilité d'une partie définie de la plateforme de données Databricks centralisée, en prenant des décisions techniques et en garantissant la livraison.. Construire et maintenir des pipelines de données de production, en exerçant un jugement architectural sur la modélisation des données et la conception des pipelines.. Engager proactivement avec les parties prenantes pour traduire les exigences en solutions de données, en servant de point de contact technique principal. Profile: - Databricks experience—Delta Lake, Workflows, and Databricks SQL; Unity Catalog familiarity preferred - 5+ years in data engineering with demonstrated ability to own problems end-to-end without close direction - Strong written and verbal communication—able to document architecture decisions and engage directly with both technical and business stakeholders - Demonstrated ability to exercise independent architectural judgment—not just ticket execution - AWS experience (S3, IAM, VPC) with ability to collaborate on infrastructure decisions - Experience building and maintaining ETL/ELT pipelines at scale, including error handling, monitoring, and data quality validation - Experience mentoring or guiding junior and mid-level data engineers - Strong data modeling skills across structured and semi-structured data sources - Infrastructure-as-code experience (Terraform preferred) - Onshore (US-based)—role requires timezone overlap, async-light communication, and direct stakeholder engagement - Familiarity with data governance patterns (Unity Catalog, data lineage, access controls) - SQL, Python, and PySpark—production pipeline implementation and performance optimization - Experience with financial data, accounting systems (NetSuite), or enterprise ERP platforms - Background building pipelines that serve AI/ML workloads (preparing data for downstream ML consumption, RAG, and LLMs) - Familiarity with data governance frameworks and compliance requirements for regulated industries - Experience working alongside or transitioning from nearshore engineering teams