Senior Data Engineer

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The Senior Data Engineer is a hands‑on technical role responsible for designing, developing, testing, deploying, and supporting scalable enterprise data solutions. The role will build and optimize data pipelines, data models, and analytics‑ready data products using Microsoft Fabric and Azure technologies while ensuring strong engineering, security, reliability, data quality, observability, and production‑readiness standards. The Senior Data Engineer will also help drive AI enablement across Data Engineering and the analytics ecosystem by applying AI‑assisted engineering capabilities, improving data discovery and insight generation, and enabling better natural‑language and AI‑powered experiences in Power BI and related analytics solutions.

• Design, develop, test, deploy, troubleshoot, and optimize enterprise data pipelines and data solutions using Microsoft Fabric, Azure, SQL, Python, Spark, and related technologies.
• Build scalable ingestion, transformation, and data processing frameworks for batch and near‑real‑time workloads across multiple enterprise data sources.
• Develop and maintain Bronze, Silver, and Gold data layers and implement enterprise modeling patterns, including Data Vault 2.0 and dimensional/curated models where appropriate.
• Develop and maintain dbt models, reusable transformation frameworks, documentation, automated tests, and engineering standards.
• Partner with technical leadership to implement enterprise data architecture patterns, engineering standards, reusable frameworks, and platform guardrails.
• Implement CI/CD, source control, automated testing, deployment pipelines, and Dev Ops practices for data engineering solutions.
• Build data quality controls, reconciliation processes, monitoring, alerting, lineage, and observability to proactively identify and resolve data issues.
• Support production operations by troubleshooting pipeline failures, performance issues, data defects, and critical incidents; perform root‑cause analysis and implement permanent fixes.
• Optimize data pipelines, SQL queries, Spark workloads, storage, and compute utilization for performance, scalability, reliability, and cost efficiency.
• Implement security, access controls, data protection, and governance requirements in partnership with architecture, governance, and security teams.
• Work closely with BI, analytics, and business teams to deliver trusted, analytics‑ready data products and support Power BI semantic models and reporting solutions.
• Support migration and modernization of legacy ETL and enterprise data warehouse workloads to Microsoft Fabric while ensuring reconciliation, business continuity, and production readiness.
• Maintain technical documentation including solution designs, data mappings, operational runbooks, support procedures, and production‑readiness artifacts.
• Apply AI‑assisted engineering capabilities to improve developer productivity, accelerate SQL/Python development, support code quality, automate documentation and testing, and improve troubleshooting and root‑cause analysis.
• Enable AI‑ready data products by ensuring data is trusted, well‑modeled, governed, documented, and accessible for AI, machine learning, natural‑language querying, and advanced analytics use cases.

Bachelor's degree in computer science, Engineering, Math or related field is required Master's degree is preferred 5+ years of experience in data engineering, data warehousing, ETL/ELT, or enterprise analytics…