Senior Data Engineer

Role & Responsibilities :

• Design, build, and optimize modern data solutions for our mid-market and enterprise clients
• Transform raw data into trusted, analytics-ready assets that power dashboards, advanced analytics, and AI use cases working primarily inside the Microsoft stack (Azure, Synapse, and Microsoft Fabric)
• Develop scalable, well-documented ETL/ELT pipelines using T-SQL, Python, Azure Data Factory/Fabric Data Pipelines, and Databricks; implement best-practice patterns for performance, security, and cost control.
• Design relational and lakehouse models; create Fabric OneLake shortcuts, medallion-style layers, and dimensional/semantic models for Power BI.
• Build automated data-quality checks, lineage, and observability metrics; contribute to CI/CD workflows in Azure DevOps or GitHub
• Gather requirements, demo iterative deliverables, document technical designs, and translate complex concepts to non-technical audiences.
• Research new Fabric capabilities, share findings in internal communities of practice, and contribute to reusable accelerators.

Qualifications :

• Bachelors degree required.
• Minimum of 3 years delivering production data solutions, preferably in a consulting or client-facing role.
• Strong SQL for data transformation and performance tuning.
• Python for data wrangling, orchestration, or notebook-based development (PySpark), and hands on ETL/ELT with at least one Microsoft service (ADF, Synapse Pipelines, Fabric Data Pipelines). Solid grasp of Azure fundamentalsstorage, networking, security, and cost management.
• Project experience with Microsoft Fabric (OneLake, Lakehouses, Data Pipelines, Notebooks, Warehouse, Power BI Direct Lake).
• Familiarity with Databricks, Delta Lake, or comparable Lakehouse technologies, and exposure to DevOps (YAML pipelines, Terraform/Bicep) and test automation frameworks.
• Experience writing unit tests for data pipelines and transformation logic, understanding or working with metadata frameworks for data governance and lineage, and integrating SaaS/ERP sources (e.g., Dynamics 365, Workday, Costpoint, SAP, NetSuite, Sage Intacct, IFS, etc.)