Senior Data Engineer

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• →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 DevOps 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 platforms, with demonstrated experience delivering production-grade data solutions.
• Strong hands-on SQL skills and experience with Python and/or PySpark for data engineering workloads.
• Experience with Microsoft Fabric, Azure Data Factory, Azure Data Lake Storage, Synapse, Databricks, or comparable modern cloud data platforms.
• Strong understanding of data modeling, dimensional modeling, data lake/lakehouse patterns, and enterprise data architecture concepts.
• Experience implementing data quality, monitoring, observability, automated testing, and production support practices.
• Experience with Git, CI/CD, DevOps, and automated deployment practices.
• Strong analytical, troubleshooting, communication, and cross-functional collaboration skills.
• Experience with or knowledge of Agile Software Development methodologies
• Strong aptitude for learning new technologies and analytics techniques
• Communication skills and ability to develop and present solutions to all levels of management
• Must be able to interact effectively and patiently with customers especially while under pressure
• The ability to work on multiple projects/tasks simultaneously to meet project deadlines for self and others as required
• Ability to establish and maintain positive working relationships with other employees.
• Strong analytical and problem-solving skills, with strict attention to accuracy and detail, and the ability to evolve data into knowledge
• Passion for delivering highly available, robust BI solutions
• Knowledge of best practices and IT operations in an always-up, always-available service

• Hands-on experience with Microsoft Fabric, OneLake, Fabric Data Engineering, Fabric Data Factory, and related platform capabilities.
• Experience with dbt Core and Data Vault 2.0.
• Experience with Microsoft Purview, metadata management, lineage, governance, and data catalog capabilities.
• Exposure to AI/ML, generative AI, Microsoft Copilot capabilities, or AI-assisted data and analytics engineering.