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Job Description
Sikich India is seeking an experienced Data Engineer to join our Data & AI practice. You will design, build, and optimize end-to-end data solutions using Microsoft’s data platforms, including Microsoft Fabric, Azure Synapse Analytics, Databricks, and Power BI. Your work will involve implementing contemporary data architecture patterns (e.g., creating robust data pipelines, and delivering insight-driven analytics to help clients make informed decisions.
Sikich () is a global company specializing in technology enabled-professional services. 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. Data Engineering & Architecture
Design and implement data solutions using ADF, Microsoft Fabric, Synapse, Databricks.
Build data models for scalable data processing, endpoint processing, and integration.
Develop and optimize data pipelines (real-time, batch, and BYOD).
Data Modeling & Analytics
Create semantic models and dimensional models in Power BI.
Platform Operations & Governance
Apply DataOps practices, monitoring, and performance tuning.
Ensure data security, quality, and governance.
Integrate predictive analytics with Azure ML where required.
Required Skills & Experience
- 5–7 years of data engineering experience (minimum 3 years in Microsoft technologies).
- Strong expertise in Microsoft Fabric, Azure Synapse Analytics, Databricks, Power BI.
- Proficiency in SQL, T-SQL, Spark SQL, Python/Scala, DAX, Power Query (M).
- Experience with real-time streaming (Event Hubs/Kafka) and batch processing.
- Microsoft Certified: Azure Data Engineer Associate / Fabric Analytics Engineer Associate / Power BI Data Analyst Associate
Databricks Certified Data Engineer Associate
Bachelor’s degree in computer science, Data Science, Engineering or related field (master’s preferred).
At 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.
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