Senior Data Engineer - Remote - (15+ Years Exp)

Senior Data EngineerLocation: 100% Remote (Mandatory Pacific Time alignment)Job Type: Contract (12 Months)About the RoleWe are seeking a highly skilled Senior Data Engineer to design, build, and scale our modern data infrastructure. In this role, you will be instrumental in developing robust ELT/ETL pipelines, optimizing data models, and establishing enterprise-grade data governance frameworks. The ideal candidate brings a software engineering mindset to data, writing clean, production-grade code, and implementing rigorous testing methodologies.Core ResponsibilitiesPipeline Engineering: Architect, deploy, and maintain scalable data pipelines capable of processing large volumes of structured and semi-structured data.Platform Optimization: Optimize data storage, compute, and query performance within Snowflake (e.g., clustering, Snowpipe, Snowflake Data Sharing) or Databricks.Code Quality: Write highly efficient, modular, and well-documented Python and SQL. Champion engineering best practices, including version control, CI/CD, and automated testing (e.g., using pytest).Cross-Functional Collaboration: Partner with upstream data producers and downstream consumers to ensure data reliability, accuracy, and adherence to data governance policies.Required QualificationsExperience: 12+ years of dedicated experience in Data Engineering, Data Architecture, or a closely related field.Python Programming (Non-Negotiable): Expert-level proficiency in Python. You must be able to write production-ready, object-oriented code. Note: Advanced Python proficiency is a strict requirement for this role; candidates without strong Python foundations will not be considered.Advanced SQL: Deep, hands-on expertise in writing complex, highly performant analytical SQL queries and navigating large relational databases.Big Data Platforms: Proven track record of designing and deploying solutions on large-scale cloud data platforms, specifically Snowflake or Databricks.Working Hours: Must be available and working during standard Pacific Time (PT) business hours.Preferred Qualifications (The "Plus" Factors)Azure Ecosystem: Hands-on experience with Microsoft Azure cloud infrastructure, including data-specific services (e.g., ADLS, Azure Data Factory) and monitoring tools (e.g., Azure Monitor).Salesforce Integration: Familiarity with extracting and ingesting data from Salesforce APIs or utilizing native connectors for enterprise reporting.