Senior Data Engineer
Listed on 2026-06-18
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IT/Tech
Data Engineering, Data Science Manager, Data Security
Job Summary
We are seeking a Senior Data Engineer to join the firm. The Senior Data Engineer contributes to the Enterprise Applications, Data, and AI Platforms group, designing scalable Microsoft Fabric data platforms. Responsibilities include establishing engineering standards, leading design, implementation, and optimization of Lakehouse, Warehouse, and Azure AI Foundry data pipelines. The role involves mentoring staff, collaborating with business and technology leaders, and delivering reliable governed products aligned with the firm’s AI strategy.
Reporting to the Senior Manager, Data Engineering, this position focuses on technical leadership and does not include direct supervisory responsibilities.
Director, Enterprise Applications, Data, and AI Platforms;
Senior Manager, Data Engineering;
Senior Manager, Automation and Development;
Senior Manager, Enterprise Applications;
Senior Applications Architect;
Senior Data Architect;
Team Lead, Workflow and Automation;
Technical Program Manager;
Project Manager;
Cloud Platform Engineer;
Security Engineer;
Business Data Experts and Business Data Sponsors
- Designing scalable and resilient data platforms with Microsoft Fabric, including Lakehouse and Warehouse solutions on One Lake, while making independent technology decisions.
- Establishing and maintaining data engineering standards, patterns, and best practices across the data engineering group and the wider EA organization.
- Designing, developing, and overseeing complex data pipelines using Fabric Data Factory, Dataflow Gen2, and Fabric Notebooks for ingestion, transformation, and advanced automation.
- Leading schema design, dimensional modeling, Medallion Architecture implementation, and semantic model development to enable analytics, reporting, and AI-related workloads effectively.
- Optimizing data performance, reliability, and cost by proactively tuning, monitoring, and validating data quality through established processes.
- Ensuring data governance, quality, and security standards are integrated into solutions, collaborating with governance leads to apply classification, lineage, and access controls.
- Designing and maintaining data pipelines supporting Azure AI Foundry workloads, including grounding datasets, vector indexing preparation, and feature data for retrieval‑augmented generation.
- Providing mentorship and guidance to junior data engineers through code reviews, design sessions, and technical coaching, enhancing the team's overall engineering quality.
- Partnering with business stakeholders to convert complex requirements into scalable data architectures while collaborating within an Agile Dev Ops model. Supporting CI/CD pipelines, automated deployments, and maintaining architecture documentation.
- Serving as a model for the Enterprise Applications team philosophy, advocating enterprise processes, procedures, security, standards, and knowledge‑first support.
- Defining and overseeing testing strategies for assigned data solutions, including quality standards, user acceptance frameworks, and validation of data accuracy.
- Leveraging AI tools like Microsoft Copilot and Claude to aid development and contribute to AI solutions on the Microsoft platform stack. Adhering to governance standards, ensuring responsible use, data classification, and implementing model deployment controls effectively.
- Hold Bachelor’s degree in a technical field; equivalent experience accepted, with ability to obtain Microsoft certifications including DP‑600, DP‑203, and AI‑900.
- Understand Data Mesh and Microsoft Purview, including domain ownership, federated governance, metadata management, cataloging, and sensitivity labeling.
- Maintain a secure workspace and willingness to travel up to 10% for offices, vendor sites, conferences, or seminars.
- Participate in scheduled release windows and production support events, including evenings or weekends, with advance notice and flexible scheduling.
- Demonstrate the ability to implement data governance, ensure quality, optimize performance, and integrate security controls into enterprise data solutions.
- Translate complex business requirements…
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