Azure Data Engineer ($50/hr)

We are seeking a skilled Azure Data Engineer to design, build, and maintain scalable data solutions in our cloud environment. The ideal candidate will have hands-on expertise in Databricks, Azure Data Factory, and Synapse, with strong engineering and problem-solving skills. This role involves creating efficient data pipelines, optimizing performance, and supporting business-critical data platforms. Key Responsibilities • Design and develop new data pipelines leveraging existing frameworks and tools. • Orchestrate and monitor pipelines using Azure Data Factory (ADF). • Build and enhance data transformations with Databricks, PySpark, and SQL to load data into Enterprise Data Lake, Delta Lake, and Synapse Analytics (DWH). • Implement unit testing, coordinate integration testing, and support UAT cycles. • Prepare technical documentation including HLDs, detailed designs, and runbooks for data pipelines. • Configure compute environments, data quality (DQ) rules, and pipeline maintenance routines. • Optimize and tune data workflows for performance and cost efficiency. • Provide production support for data platforms and pipelines. Required Skills & Experience • 3–5 years (Associate) or 5–7 years (Senior) of hands-on data engineering experience. • Strong knowledge of Databricks (Data Engineering, DLT), Azure Data Factory, SQL, and PySpark. • Experience with Azure Synapse (Dedicated SQL Pool), Azure DevOps, Python, Azure Function Apps, and Azure Logic Apps. • Familiarity with Precisely (nice to have). • Solid understanding of data modeling, data integration, and performance tuning. • Strong problem-solving and debugging skills in a production environment. • Degree in Engineering, Computer Science, or a related field. Nice to Have • Exposure to data quality and governance tools such as Precisely. • Experience with enterprise-scale data platforms and large datasets.