Data Engineer

Title- Data Engineer Location - Redmond ,WA ( Open for WFM -Need to work in PST time zone Job description The role is strongly aligned with Microsoft technologies, so the candidate’s experience should be relevant to Microsoft products, Azure data stack, and MSFT engineering culture. Key Responsibilities • Design, develop, and maintain scalable big data solutions using Apache Spark and Scala. • Implement complex SQL queries for data transformation and analytics. • Develop and optimize Power BI dashboards for business reporting and visualization. • Collaborate with cross-functional teams to integrate data pipelines and reporting solutions. • Ensure data quality, security, and compliance across all systems. Required Skills & Experience • Strong proficiency in Apache Spark with hands-on experience in Scala. • Solid understanding of SQL for data manipulation and analysis. • Experience in Power BI for creating interactive reports and dashboards. • Familiarity with distributed computing concepts and big data ecosystems (Hadoop, Hive, etc.). • Ability to work with large datasets and optimize data workflows. Highly Desirable • Spark Performance Tuning Expertise: Proven ability to optimize Spark jobs for efficiency and scalability. • Knowledge of cluster resource management and troubleshooting performance bottlenecks. • Experience with Azure cloud services for big data solutions (e.g., Azure Data Lake, Azure Databricks, Synapse Analytics). • Exposure to other cloud platforms (AWS or GCP) is a plus. • Experience working in financial domain or with ERP systems (e.g., SAP, Oracle ERP). • Understanding of compliance and regulatory requirements in financial data processing. Additional Qualifications • Strong problem-solving and analytical skills. • Excellent communication and collaboration abilities. • Recent Microsoft experience • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. Key skills: Synapse, IAAS VM, SQL Server, ADLS Gen 2, Azure Automation account runbooks using PowerShell, Spark, Scala programming.