What You'll Do
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.
Requirements
What you’ll Bring
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
How to Apply:
Share your philosophy on developing data infrastructure, the methodologies you utilize, and provide concrete examples of data systems you've built that have delivered tangible results.
Tell us why you are interested to join Suzega
What Happens Next:
We will review applications
If shortlisted, you'll participate in two virtual interviews with our Trusted Interviewers
You will have to go through a coding interview
We will aim to complete our selection process within two weeks and notify you of our decision
Why This Matters:
At Suzega, we're not just building better AI—we're thinking about how AI can work better with people and society. Are you ready to help shape what AI can and should do? Do you want to use your technical skills to make a real difference?
If so, we'd love to hear from you.
This is more than a job. It's a chance to shape the future.
Benefits
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