Senior Data Engineer with strong Azure Key Responsibilities Develop and maintain scalable ETL (Extract, Transform, Load) processes to efficiently extract data from diverse sources, transform it as required and load it into data warehouses or analytical systems. Design and optimize database architectures and data pipelines to ensure high performance, availability and security while supporting structured and unstructured data. Build and maintain robust ETL/ELT pipelines using Fabric Pipelines, Azure Data Factory, and Synapse. Implement secure data architectures using Roles-based Access Controls (RBAC), Key Vault, Private Endpoints. Integrate data from APIs, third-party platforms, and hybrid (on-prem/cloud) systems. Develop data workflows using Python, SQL, and Spark, selecting appropriate frameworks based on workload characteristics. Drive cost-efficient, low-latency analytics through partition-aligned Delta storage, columnstore-optimized warehouse tables, DirectLake semantic access, and SCD-managed dimensional models, ensuring predicate pushdown, partition elimination, and minimal data movement across the query execution lifecycle. Implement secure data architectures using: RBAC and row/column/object-level security (RLS/CLS/OLS), Azure Key Vault, Private Endpoints, Managed Identities. Implement CI/CD pipelines for data platforms using Azure DevOps or GitHub. Establish automated deployment, environment promotion, and testing strategies. Support downstream semantic models and reporting layers by delivering well-modeled, performant, and governed data structures. Partner with analytics and AI teams to deliver trusted, production-ready data products. Ensure platform reliability through constraint-driven data validation, fault-tolerant pipeline orchestration, and telemetry-backed observability, enabling anomaly detection, automated alerting, and lineage-driven root cause analysis across distributed data workloads. Lead design decisions and influence enterprise data architecture standards. Collaborate with engineers, analysts, and business stakeholders to translate requirements into scalable solutions. Mentor junior engineers and contribute to engineering excellence and knowledge sharing. Operate effectively in Agile delivery environments. Required Qualifications 8+ years of experience in data, software, or platform engineering. 5+ years building production data solutions on the Microsoft/Azure stack. Strong experience with Microsoft Fabric and at least two of: Azure Data Factory, Synapse, Databricks, Azure SQL, Power BI. Advanced proficiency in SQL and Python (delta-rs, PyArrow, Polars, DuckDB, Pandas, and NumPy). Proven experience designing modern data architectures (lakehouse, medallion, etc.). Hands-on experience with CI/CD, Git workflows, and environment promotion. Experience implementing enterprise security, identity, and access controls. Strong troubleshooting, performance tuning, and root cause analysis skills. Experience working in regulated or high-scale environments. Preferred Qualifications Certifications: DP-700 (Fabric Data Engineer) - preferred. DP-600, DP-203 - preferred.