Senior Data Engineer

Role Summary

ATL Technology is building a modern Microsoft Azure and Fabric-based enterprise data platform to become the digital backbone for operational, financial, quality, commercial, and executive decision-making. The Senior Data Engineer will be the hands-on technical leader responsible for designing, building, and operating this foundation.

This role is more than traditional ETL development. The successful candidate will establish scalable data pipelines, mature ATL’s Bronze/Silver/Gold data architecture, integrate critical business systems, implement data quality controls, and enable analytics, automation, and AI initiatives across ATL’s global operations.

Why this role matters: You will help create ATL’s internal data engineering capability, reduce reliance on manually maintained Excel-based reporting, and provide trusted data foundations for executive reporting, operational KPIs, and future AI use cases.

Key Responsibilities

Enterprise Data Platform

• Design, build, and maintain scalable data pipelines and data integration patterns using Microsoft Azure and Microsoft Fabric.
• Develop ingestion, transformation, orchestration, monitoring, and deployment standards for enterprise data workloads.
• Build and mature ATL’s Bronze, Silver, and Gold data layers with reusable, well-documented engineering practices.
• Drive platform reliability, observability, performance optimization, and operational support practices.

Business System Integration

• Integrate data from Infor ERP, Workday, Autodesk Fusion, Dynamics CRM, SharePoint, manufacturing systems, and future enterprise platforms.
• Develop API-based and connector-based integrations where appropriate.
• Partner with application owners and business stakeholders to understand source system logic, data definitions, and integration requirements.
• Monitor pipeline health and proactively resolve data integration issues.

Data Modeling & Analytics Enablement

• Design curated datasets and analytical models for Power BI and enterprise reporting.
• Support dimensional modeling and business logic for certified data assets.
• Partner with Finance, Operations, Quality, Engineering, Sales, and leadership teams to translate business needs into reliable data products.
• Enable governed self-service analytics by delivering trusted, consistent, and reusable data assets.

Data Quality, Governance & Compliance

• Implement data quality checks, reconciliation controls, lineage, metadata, documentation, and issue resolution practices.
• Support master data and data governance initiatives in partnership with business data owners and stewards.
• Design data solutions that support ATL’s regulated environment, including quality, privacy, security, and compliance considerations.
• Promote DataOps practices including source control, testing, CI/CD, and release discipline.

AI & Automation Enablement

• Create reliable data foundations for AI, Copilot, automation, and advanced analytics initiatives.
• Identify opportunities to automate manual reporting and operational data processes.
• Support future predictive analytics and machine learning use cases through well-structured, governed data assets.

Technical Leadership

• Serve as a senior hands-on technical leader for ATL’s enterprise data platform.
• Partner with external consulting partners while building ATL’s long-term internal capability.
• Mentor future data engineering team members and help establish standards for the data engineering discipline.
• Influence architecture, tooling, and roadmap decisions with a practical business-outcome mindset.

Qualifications

• 7+ years of data engineering experience, including experience building or significantly maturing enterprise data platforms.
• Strong hands-on experience with SQL, Python, ETL/ELT design, data modeling, and enterprise integration patterns.
• Experience with Microsoft Azure data services, including Azure Data Factory, Azure Data Lake, Synapse Analytics and/or Microsoft Fabric.
• Experience supporting global, multi-site organizations and working directly with business stakeholders.
• Strong communication skills with the ability to explain technical concepts clearly to both technical and non-technical audiences.
• Demonstrated ability to operate independently, make sound technical decisions, and connect platform work to business outcomes.

Experience

• Required: data pipeline development, orchestration, monitoring, performance tuning, and data quality implementation.
• Required: Git-based source control and CI/CD or DataOps practices using Azure DevOps or similar tooling.
• Preferred: Infor CSI/Syteline or other ERP integration experience.
• Preferred: manufacturing, medical device, life sciences, or regulated industry experience.
• Preferred: Power BI semantic models, dimensional modeling, Kimball methodology, Microsoft Purview, MDM, or data cataloging experience.
• Preferred: experience enabling AI, machine learning, or Copilot use cases through trusted enterprise data.

Education

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field preferred.
• Equivalent practical experience will be considered in lieu of a degree.

Certifications (or demonstratable equivalent experience)

• Microsoft Certified: Azure Data Engineer Associate preferred.
• Microsoft Fabric Analytics Engineer Associate preferred.
• Relevant Azure, Power BI, data governance, or cloud architecture certifications are a plus.