Sr. Data Engineer

Senior Data Engineer Hybrid preferred. This role is not eligible for employment-based immigration sponsorship. Applicants must be legally authorized to work in the United States without employer sponsorship, now or in the future. Responsibilities As a Sr. Data Engineer, you will own the design and delivery of complex data engineering solutions that power enterprise analytics, AI, and reporting capabilities. Reporting to the Lead Data Engineer, you will drive technical decisions, set engineering standards, and ensure the reliability and scalability of data platform across 40+ integrated enterprise source systems. This role demands deep technical mastery in SQL, Python, and Azure cloud data engineering, combined with a product orientation—understanding how the data assets you build translate into decisions, reports, and AI outputs for the business. You will mentor Data Engineers, contribute to architectural direction, and serve as a technical anchor for delivery across the team's sprint cycles. Education Bachelor's degree in computer science, Data Science, Information Technology, or a related quantitative field. Experience 6+ years of progressive experience in data engineering with demonstrated ownership of complex, production-grade data platforms. Expert-level SQL (query optimization, indexing strategy, execution plans) and Python (PySpark, pipeline frameworks, testing). Deep hands-on experience with Azure data services: Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage. Proven experience designing dimensional data models and data lake architecture at enterprise scale. Experience building data pipelines that directly support machine learning feature engineering and model serving. Strong background in data quality engineering—automated validation, SLA enforcement, and lineage tracking. Experience with relational databases (SQL Server, Oracle) and migration from legacy to cloud-native platforms. Certifications & Licenses Microsoft Certified: Azure Data Engineer Associate Databricks Certified Associate Developer for Apache Spark Knowledge Advanced SQL and Python for enterprise-scale data engineering—optimization, testing, and framework design. Azure data platform architecture in depth—ADF, Databricks, Synapse, ADLS, and their integration patterns. Modern data platform paradigms—data lake, medallion architecture, data mesh concepts, and consumption layer design. Machine learning pipeline requirements—feature engineering, training data preparation, and model data dependencies. Data governance frameworks—metadata management, lineage, cataloging, access control, and regulatory compliance (HIPAA). Agile engineering practices—sprint delivery, DevOps hygiene, CI/CD for data pipelines, and technical documentation standards. Skills Cultural competency and the ability to communicate effectively in a culturally sensitive manner with both individuals and groups from diverse backgrounds. Architect and deliver complex, production-grade data pipelines that meet enterprise reliability and performance standards. Design scalable data models and platform structures that serve analytics, reporting, and AI consumption patterns simultaneously. Lead data quality engineering—automated testing, validation frameworks, SLA monitoring, and incident response. Mentor and elevate Data Engineers through code review, architectural feedback, and knowledge transfer. Translate product and analytical requirements into sound engineering designs and delivery plans. For a complete and detailed Position Description - Please Apply with Resume Perennial Resources International