Senior Data Engineer - US

Suzega; United States; Remote; USD 120,000 - 170,000; Full time

Job summary

Suzega is seeking a data engineering professional to own end-to-end data modernization on Azure Synapse or Fabric, creating scalable pipelines and governed data products for downstream AI/ML and semantic search use cases.

You will design, implement, and monitor ETL/ELT pipelines, manage medallion architecture, and collaborate with AI/ML teams to ground LLM applications with vector embeddings and semantic metadata.

Qualifications

• Expertise in T-SQL with deep experience using Azure Synapse Dedicated SQL Pools and Azure Data Hub.
• Strong Python proficiency for data manipulation, AI orchestration, and pipeline development (PySpark, Pandas).
• Hands-on experience across the Azure Stack, including Synapse Pipelines, ADLS Gen2, and Azure Data Hub for enterprise data warehouse ops.

Responsibilities

• Design, build, and optimize scalable ETL/ELT pipelines in Azure Synapse.
• Develop medallion (Bronze-Silver-Gold) architectures for analytics workloads.
• Integrate AI capabilities into data operations, incl. incident triage and cost-reduction suggestions.
• Implement data quality checks and monitoring to ensure trustworthy datasets.
• Administer data warehouses, data lakes, and relational plus NoSQL DBs.
• Operate workflow orchestration tools like Airflow, Prefect, or Dagster.

Skills

T-SQL

Azure Synapse

Azure Data Hub

NoSQL databases

Python

PySpark

Pandas

Airflow

Prefect

Dagster

AI integration patterns

Data warehousing

Data modeling

Data quality

Tools

Airflow

Dagster

Prefect

PySpark

Job description

Role overview

Take ownership of end-to-end data modernization on Azure Synapse or Fabric, translating client requirements into scalable pipelines and delivering governed, high-quality data products. The work supports downstream AI/ML applications and natural-language search experiences.

Responsibilities

• Design, build, and optimize scalable ETL/ELT 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) tuned for high-performance SQL analytics and AI-ready 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 that keep datasets trustworthy.
• Administer data warehouses, data lakes, and relational plus NoSQL databases.
• Operate workflow orchestration tools such as Airflow, Prefect, or Dagster for scheduling and monitoring pipelines.
• Collaborate with AI/ML engineers to ground large language model applications through vector embeddings and semantic search metadata.
• Maintain data security and compliance standards, and tune storage plus processing costs using FinOps automation.
• Troubleshoot and resolve data issues independently.

Requirements

• Expertise in T-SQL with deep experience using Azure Synapse Dedicated SQL Pools, Azure Data Hub, and relational plus NoSQL databases.
• Strong Python proficiency for data manipulation, AI orchestration, and pipeline development, including PySpark and Pandas.
• Hands-on experience across the Azure Stack, including Synapse Pipelines, ADLS Gen2, and Azure Data Hub for enterprise data warehouse 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 at scale.
• Solid grasp of data warehousing concepts, data modeling, and data quality principles.
• Ability to work independently and take ownership of data infrastructure components.