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SeniorFull-timePythonAWSAzureData ScienceCI/CDGitAIML
Salary Range
$140,000 - $210,000 /year
About the Role
Shield AI is seeking a Senior Data Engineer to architect and implement secure, scalable data systems in Microsoft Fabric that power Finance, FP&A, Accounting, Program Management, and Executive reporting. This role involves designing the backbone of a mission-critical analytics platform that supports executive decision-making, forecast accuracy, compliance reporting, and scalable AI adoption.
Key Responsibilities
- →Architect and implement end-to-end ELT/ETL pipelines in Microsoft Fabric Lakehouse environments using Python, SQL, and PySpark
- →Design and optimize medallion architectures for enterprise-scale financial and corporate data
- →Build secure, automated ingestion frameworks integrating ERP, FP&A, project accounting, and operational systems
- →Design orchestration and monitoring frameworks to ensure reliability, observability, and audit readiness
- →Optimize Fabric compute unit usage, query folding strategies, partitioning, indexing, and workload isolation
- →Develop production-grade data models that support BI, self-service analytics, and advanced statistical modeling
- →Collaborate on productionizing ML-enabled workflows such as GL classification, anomaly detection, and forecasting
- →Implement data quality validation, reconciliation automation, and governance controls aligned with compliance standards
- →Partner with Finance and Product stakeholders to translate business needs into scalable technical solutions
- →Mentor engineers and contribute to engineering standards, CI/CD, code review practices, and documentation
Requirements
- ✓7+ years of experience in data engineering or cloud data architecture roles
- ✓Expert-level proficiency in SQL and Python; strong hands-on experience with PySpark
- ✓Production experience in Microsoft Fabric, Databricks, Snowflake, or comparable cloud data platforms
- ✓Strong understanding of dimensional modeling, star schemas, and analytics engineering best practices
- ✓Experience designing secure, compliance-aware data platforms in regulated environments
- ✓Demonstrated ability to independently own architectural decisions and deliver enterprise-grade systems
- ✓Working knowledge of statistics, model evaluation concepts, and ML production workflows
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