Azure Data Engineer - Con - MFT KGS CH
Azure Data Engineering is responsible for leading the design, delivery, and operational excellence of enterprise-scale data platforms on Microsoft Azure. This role combines hands-on technical leadership, team management, and stakeholder engagement, with a strong focus on enabling AI and Generative AI (GenAI) initiatives through high-quality, secure, and reliable data pipelines.
The Assistant Manager oversees data engineering teams, defines technical standards, and ensures that data platforms effectively support LLM training, embeddings, inference pipelines, and AI-enabled applications, while meeting enterprise security, governance, and performance expectations.
Interact with multiple stakeholders and manage the end-to-end data project delivery from project requirements, solutioning and execution and hand off to operations.
Bachelor's degree in computer science, Engineering, Information Systems, or a related technical field, or equivalent practical experience.
Experience with Azure cloud services, specifically data storage and data processing solutions.
Strong knowledge of data warehousing and ETL (Extract, Transform, Load) concepts.
Handson experience with SQL, Python and PySpark.
Understanding of GenAI and LLM data concepts, including training data, embeddings, and inference pipelines.
Strong understanding of data security and privacy best practice.
Experience with monitoring and troubleshooting data pipelines.
Strong problemsolving and analytical skills.
Effective communication skills to collaborate with crossfunctional teams.
Experience with data governance is a plus.
Proven experience leading and mentoring teams.
Strong communication and stakeholder management skills.
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Own the architecture, design, and delivery of scalable data storage and processing solutions using Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics, and Azure Databricks.
Define and enforce data engineering standards, best practices, and design patterns across teams.
Provide technical leadership and oversight for complex ETL/ELT pipelines.
Lead data engineering support for AI and GenAI workloads, including preparation and management of training datasets, embeddings, and inference pipelines.
Partner with data scientists, AI engineers, and solution architects to meet AI performance and governance requirements.
Manage, mentor, and grow a team of Azure Data Engineers.
Plan capacity, allocate work, and ensure timely delivery of initiatives.
Drive adherence to Agile delivery practices.
Drive optimization of storage, compute, and pipelines for performance and cost efficiency.
Review and approve designs with long-term sustainability in mind.
