Senior Data Engineer

RiseMe; Minnesota; Hybrid; USD 120,000 - 180,000; Full time

Job summary

RiseMe is seeking a Senior Data Engineer to design, build, and operate scalable data pipelines and data products that power analytics, reporting, and AI initiatives. You will contribute to automation, data quality, metadata management, and governance while expanding your skills in governance and AI-enabled automation.

The role supports Azure/Microsoft Fabric currently, with experience on AWS or Databricks considered.

Responsibilities

• Design, build, and operate batch and streaming data pipelines on modern cloud data platforms.
• Develop robust ETL/ELT processes using SQL, Python, and PySpark with strong error handling, monitoring, and cost awareness.
• Implement layered / medallion data architectures and analytics-ready data models to support BI and AI workloads.
• Partner with analysts and data scientists to deliver trusted, production-grade data assets.
• Partner with platform and business stakeholders to support and enhance data governance practices using Microsoft Purview or comparable governance platforms.
• Contribute to governance standards and best practices for data products, analytics solutions, AI/ML features, and agent-based workflows as organizational capabilities evolve.
• Help incorporate governance considerations into platform workflows and data engineering practices rather than treating governance as an after-the-fact process.
• Support ongoing data and AI governance initiatives and grow into greater ownership of governance patterns as experience and organizational standards evolve.
• Contribute to the design and implementation of AI-enabled tools and automation workflows that support data platform and governance operations.
• Partner with technical teams to explore and develop automation that assists with metadata enrichment, data quality checks, anomaly detection, and governance workflows.
• Help ensure AI-enabled tools and automation operate only on approved, governed data sources with appropriate logging and auditability.
• Build knowledge of evolving AI governance patterns, including agent lifecycle management and input/output traceability, with support from the broader team.
• Implement and maintain CI/CD pipelines for data and AI assets.
• Promote platform enablement.

Job description

Senior Data Engineer

The Role

We are looking for a Senior Data Engineer with a strong foundation in modern data engineering, DevOps, and cloud data platforms. The primary focus of this role is designing, building, and operating scalable, reliable data pipelines and data products that support analytics, reporting, and AI initiatives across the organization.

In addition to building and operating reliable data pipelines, this role will contribute to automation, data quality, metadata management, and governance workflows. The successful candidate will bring strong data engineering expertise and an interest in expanding their knowledge of data governance and AI-enabled automation as these capabilities continue to evolve.

While our current platform is centered on Azure and Microsoft Fabric, we welcome candidates with strong data engineering experience on AWS, Databricks, or other modern data platforms, provided their skills are transferable and they demonstrate strong data engineering fundamentals.

How This Role Is Different

This role is for a senior data engineer who enjoys building modern data platforms, scalable data pipelines, and trusted data products. The primary focus will be delivering high-quality data engineering solutions that support business, analytics, and AI needs. The individual will also have opportunities to contribute to governance patterns, platform automation, and controls embedded within CI/CD processes while developing these skills as the organization's capabilities mature.

Key Responsibilities

• Data Engineering Foundations
• Data Governance & Platform Stewardship
• AI & Automation Enablement
• DevOps & Platform Enablement
• Design, build, and operate batch and streaming data pipelines on modern cloud data platforms.
• Develop robust ETL/ELT processes using SQL, Python, and PySpark with strong error handling, monitoring, and cost awareness.
• Implement layered / medallion data architectures and analytics-ready data models to support BI and AI workloads.
• Partner with analysts and data scientists to deliver trusted, production-grade data assets.

Data & AI Governance (Primary Focus)

• Partner with platform and business stakeholders to support and enhance data governance practices using Microsoft Purview or comparable governance platforms.
• Contribute to governance standards and best practices for data products, analytics solutions, AI/ML features, and agent-based workflows as organizational capabilities continue to evolve.
• Help incorporate governance considerations into platform workflows and data engineering practices rather than treating governance as an after-the-fact process.
• Support ongoing data and AI governance initiatives and grow into greater ownership of governance patterns as experience and organizational standards evolve.

AI Agents & Automation

• Contribute to the design and implementation of AI-enabled tools and automation workflows that support data platform and governance operations.
• Partner with technical teams to explore and develop automation that assists with metadata enrichment, data quality checks, anomaly detection, and governance workflows.
• Help ensure AI-enabled tools and automation operate only on approved, governed data sources with appropriate logging and auditability.
• Build knowledge of evolving AI governance patterns, including agent lifecycle management and input/output traceability, with support from the broader team.

DevOps & Platform Enablement

• Implement and maintain CI/CD pipelines for data and AI assets.
• Prom