Data Engineer

Sikich draws on a diverse portfolio of technology solutions to deliver transformative digital strategies and ranks as one of the largest CPA firms in the United States. Our dynamic environment attracts top-notch employees who enjoy being at the cutting edge and seeing every day how their work makes a difference.\n\nKey Responsibilities\nData Engineering & Architecture\nDesign and implement data solutions using ADF, Microsoft Fabric, Synapse, Databricks.\nBuild data models for scalable data processing, endpoint processing, and integration.\nDevelop and optimize data pipelines (real-time, batch, and BYOD).\nData Modeling & Analytics\nCreate semantic models and dimensional models in Power BI.\nBuild enterprise dashboards, paginated reports, and self-service analytics solutions.\nImplement row-level security, complex DAX measures, and model optimizations.\nPlatform Operations & Governance\nApply DataOps practices, monitoring, and performance tuning.\nEnsure data security, quality, and governance.\nIntegrate predictive analytics with Azure ML where required.\n\nRequired Skills & Experience\n5–7 years of data engineering experience (minimum 3 years in Microsoft technologies).\nStrong expertise in Microsoft Fabric, Azure Synapse Analytics, Databricks, Power BI.\nProficiency in SQL, T-SQL, Spark SQL, Python/Scala, DAX, Power Query (M).\nExperience with real-time streaming (Event Hubs/Kafka) and batch processing.\nProven track record in implementing medallion architecture and enterprise BI solutions.\n\nPreferred Certifications (nice to have)\nMicrosoft Certified: Azure Data Engineer Associate / Fabric Analytics Engineer Associate / Power BI Data Analyst Associate\nDatabricks Certified Data Engineer Associate\n\nQualifications\nBachelor’s degree in computer science, Data Science, Engineering or related field (master’s preferred).\nStrong problem-solving, communication, and client-facing skills.\n\nWhy Join Us?\nAt Sikich, you will work on cutting-edge Microsoft data projects, collaborate with global teams, and contribute to solutions that shape the future of data-driven business decisions. We value innovation, collaboration, and continuous learning.