Senior Data Engineer - US

Suzega

3d•Remote

About The Position

At Suzega, we are looking for a Senior Data Engineer to join our team. This role is crucial in shaping the future of AI by ensuring it works better with people and society. You will leverage your technical skills to make a real difference in how AI is developed and utilized. This is more than just a job; it's an opportunity to contribute to a significant technological advancement. The position is remote, allowing you to work from anywhere in the US.

Requirements

Expertise in T-SQL and deep experience with Azure Synapse Dedicated SQL Pools, Azure Data Hub, and relational/NoSQL databases.
Strong proficiency in Python for data manipulation, AI orchestration, and pipeline development (e.g., PySpark, Pandas).
Hands-on experience with the Azure Stack, including Synapse Pipelines, ADLS Gen2, and Azure Data Hub for enterprise-scale DWH operations.
Familiarity with AI integration patterns, such as prompt engineering, vector databases, and semantic layer management for natural-language query tools.
Experience building and managing data pipelines and ETL/ELT processes.
Familiarity with data warehousing concepts and data modeling.
Understanding of data quality principles.
Ability to work independently and take ownership of data infrastructure components.

Responsibilities

Design, build, and optimize scalable ETL/ELT data pipelines using advanced T-SQL and Python within Azure Synapse Dedicated SQL Pools and Azure Data Hub.
Develop and manage medallion architecture schemas (Bronze, Silver, Gold) optimized for high-performance SQL analytics and AI-powered workloads.
Integrate AI capabilities into data operations, including automated incident triage, cost-reduction recommendations, and proactive pipeline monitoring.
Implement data quality checks and monitoring frameworks.
Manage and administer data warehouses, data lakes, and databases (SQL/NoSQL).
Implement and manage workflow orchestration tools (e.g., Airflow, Prefect, Dagster) for scheduling and monitoring data pipelines.
Collaborate with AI/ML Engineers to ground LLM applications in governed data through vector embeddings and semantic search metadata.
Ensure data security and compliance standards are met.
Optimize storage and processing costs across the Azure Stack, utilizing FinOps automation and workload tuning.
Write efficient and maintainable Python code for data processing tasks.
Work independently to troubleshoot and resolve data-related issues.