Data Engineer

Job Purpose

FAC Services is expanding its engineering capability with a strategic hire focused on quality engineering across the data platform and Azure ecosystem. This role is not limited to traditional QA. It is a hands-on engineering position responsible for building confidence in how data moves, transforms, surfaces through APIs, and is monitored across the platform.

Primary Responsibilities:

The Data Quality Engineer II will play a key role in ensuring the reliability, integrity, security, and observability of the ATLAS data mart, supporting services, and related Azure-based infrastructure. This person will work across Microsoft Fabric, Azure, telemetry pipelines, APIs, and hybrid/cloud-connected services to design scalable validation patterns, automate quality controls, and strengthen operational trust in the platform.

This role requires a strong engineer who can move comfortably between data validation, API testing, infrastructure automation, telemetry, and reliability engineering. The ideal candidate is not just executing test cases but helping define what “good” looks like.

Data Platform Quality Engineering

• Design and implement automated quality controls for mirrored data, ETL/ELT workflows, semantic models, and downstream data products.
• Validate data accuracy, completeness, conformance, lineage, and transformation logic across medallion and semantic layers.
• Build repeatable tests that compare platform outputs to source-system truth, including view-level and API-served data validation.
• Partner with data engineers and platform engineers to embed quality checks into the delivery lifecycle rather than treating validation as a final step.
• Help define practical quality standards, thresholds, and monitoring patterns that support trusted production use of the data platform.

API and Data Access Validation

• Test API endpoints that expose governed platform data, including functional, integration, regression, and data consistency validation.
• Verify that API responses align with underlying platform logic, expected security boundaries, and consumer-specific data contracts.
• Validate filtering, access patterns, error handling, and performance under different conditions.
• Contribute to test automation for GraphQL and REST-based interfaces using tools such as Postman, Swagger, and custom Python or PowerShell based validation frameworks.

Telemetry, Monitoring, and Reliability

• Engineer and validate telemetry patterns that improve visibility into platform health, pipeline behavior, API reliability, and cloud operations.
• Support testing and validation of logs, alerts, and diagnostic outputs across Azure, Microsoft Fabric, Event Hub, and related monitoring pipelines.
• Help ensure operational events, failures, and security-relevant activity are observable and actionable.
• Contribute to platform readiness by validating alerts, telemetry coverage, and production support signals across cloud and hybrid-connected workloads.

CI/CD and Engineering Enablement

• Embed data and platform quality checks into Azure DevOps pipelines and release workflows.
• Help establish test-driven and automation-first engineering practices for data pipelines, APIs, and infrastructure changes.
• Build reusable scripts, frameworks, and validation utilities that reduce manual effort and release confidence.
• Partner with engineering teams to shift quality earlier into design, build, and deployment processes.

Collaboration and Technical Leadership

• Work cross-functionally with Infrastructure, DevOps, Data Engineering, Security, and QA to align on quality expectations across the platform.
• Act as a technical leader in defining scalable approaches to validation, monitoring, and platform trust.
• Mentor team members in modern quality engineering practices for cloud, data, and automation-heavy environments.
• Lead by example through strong engineering discipline, clear communication, and continuous improvement.

Qualifications:

To perform this job successfully, an individual must be able to perform each primary duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required.

Experience

• 3 years in QA engineering, specializing in data testing/infrastructure
• Extensive ETL/ELT testing, data validation, and quality frameworks experience
• Skilled in SQL and scripting (Python, PowerShell)
• Knowledge of CI/CD tools and workflows (Git, Azure DevOps)
• API testing experience; familiar with Swagger documentation
• Understanding of IaC tools (Terraform, ARM, Bicep)
• Microsoft Azure expertise
• Strong communicator and effective team player

This position requires in person office attendance in Madison, WI.