Job Description Insight Global is seeking a Senior Data Engineer to design, build, and scale robust data solutions on Microsoft Azure. You’ll own modern data pipelines and models that power analytics and reporting across the business. The ideal candidate is hands‑on with SQL databases, Azure Data Lake Storage, Azure Data Factory (ADF), and Power BI, and is comfortable operating in an engineering culture that values reliability, performance, and strong DevOps practices. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements - 5+ years of professional experience in data engineering or closely related roles. - Experience with Databricks for large‑scale transformations. - Advanced expertise with SQL databases (e.g., Azure SQL/SQL Server) including query optimization and performance tuning. - Hands‑on experience with Azure Data Lake Storage (ADLS Gen2) and Azure Data Factory (ADF). - Strong experience delivering analytics with Power BI (datasets, data models, DAX, security). - Practical Azure DevOps experience (Git, Repos, Pipelines) for CI/CD of data solutions. - Oracle experience (PL/SQL, data extraction and integration) in hybrid/cloud data architectures. - Solid understanding of data warehousing concepts (dimensional modeling, SCD, partitioning) and ETL/ELT design patterns. - Proficiency in at least one scripting/programming language commonly used in data engineering (e.g., Python or SQL‑centric frameworks) for automation and data transformations. - Strong ownership, communication, and collaboration skills in distributed teams. Experience with Power BI deployment pipelines and governance at scale. Familiarity with Application Insights telemetry, Log Analytics, and end‑to‑end observability for data workloads. Data quality tooling (e.g., unit/integration testing, validation frameworks), and experience with metadata/catalog solutions. Background in optimizing cost on Azure (storage tiers, pipeline orchestration strategies, caching).