Azure Cosmos Data Engineer

Job Title: Azure Cosmos Data Engineer Location: Remote Duration: 6-12 month contract with multiple extensions Rate: $50/hr. on W2 (NO C2C) Azure Cosmos Data engineer • Expertise in Azure Synapse, Cosmos DB for potential role • Experience in international data mapping, data conversion, set up is preferred. • Azure Synapse Analytics: • Data integration, big data processing. • Databricks: Apache Spark, Delta Lake, notebooks. • SQL: Advanced querying, performance optimization, database management. • PySpark: ETL processes, data transformation, performance tuning. • Data Pipelines: Design, development, orchestration, monitoring. • Data Modeling & Database Design: Schema design, normalization/denormalization. • ETL/ELT Tools: Azure Data Factory. • NoSQL Database: Azure Cosmos DB • Relational Database: SQL Server and Oracle • Version Control Systems: Git proficiency. Must-Have Experience • Strong experience building end-to-end data pipelines (ETL/ELT) • Hands-on with cloud platforms (Azure preferred) • Experience working on enterprise/global applications with large datasets Core Technical Skills (High Priority) • Strong hands-on experience with Azure Cosmos DB (required) Min 2 years • Experience with Azure Synapse Analytics (required) for analytics and data warehousing • Experience with Azure Data Factory, Databricks (PySpark), and Data Lake • Strong programming in Python, SQL, PySpark • Good understanding of SQL + NoSQL databases Data Architecture & Global Use Case Experience • Experience in international data mapping / data standardization across regions • Exposure to distributed systems and multi-region data processing • Understanding of data partitioning, replication, and performance optimization • Experience supporting global applications / enterprise-wide analytics platforms Soft Skills / Functional Fit • Strong collaboration with cross-functional and global teams • Ability to translate business requirements into data solutions • Experience working in fast-paced, high-impact environments • Ownership mindset (handling large-scale, business-critical pipelines)