Sr Data Engineer

Position: Sr Data Engineer Location: San Jose, CA Contract: 12+ Months • Design and implement scalable data models that unify data across multiple business domains into a consistent, analytics-ready layer. • Build and optimize data pipelines using Databricks (Spark) to support batch and near real-time processing. • Develop and maintain curated datasets (gold layer) to support reporting, analytics, and machine learning use cases. • Partner closely with data scientists to enable feature engineering, model training, and production ML workflows. • Translate ambiguous business and analytical requirements into scalable, reusable data models. • Implement data quality, validation, and observability frameworks to ensure trusted data assets. • Optimize data performance, storage, and compute costs within the Databricks environment. • Apply best practices in data modeling (dimensional, semantic, or Data Vault where appropriate). • Contribute to data governance, metadata management, and data lineage standards. • Collaborate with cross-functional teams (Analytics, Engineering, Business stakeholders) to deliver high-impact data solutions. Requirements Experience • 10+ years of experience in data engineering with strong data modeling expertise. • Hands-on experience with Databricks, Spark, and cloud data platforms (AWS, Azure, or GCP). • Strong SQL and Python skills for data transformation and pipeline development. • Proven experience building unified/curated data models across multiple data sources. • Experience working closely with data scientists and supporting ML workflows. • Solid understanding of data architecture patterns (lakehouse, medallion architecture). • Experience with orchestration tools (Airflow, ADF, or similar). • Strong problem-solving skills and ability to work in ambiguous environments.