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.