Data Engineer
About The Position
NAC is seeking an experienced Data Engineer to design, build, and optimize data solutions on Microsoft Azure and Microsoft Fabric. The position supports the use of firm data for advanced analytics, reporting, and digital transformation. The engineer will develop automated, reliable, scalable, and high-quality data solutions, including ingestion from business systems into a governed lakehouse and optimization of data models and datasets used for reporting. Reporting to the Data Leader, the role works closely with IT leadership, the data team, and resources supporting data architecture and governance. Work includes building and maintaining data pipelines and integrations; implementing Microsoft Fabric lakehouse, warehouse, and analytics capabilities; developing curated datasets and semantic models; optimizing data architecture and transformations; maintaining data quality, security, and governance practices; supporting migration of legacy systems; collaborating with stakeholders; documenting solutions; and following source control and deployment practices. The role is based in one of NAC’s four offices: Columbus, Los Angeles, Seattle, or Spokane. The work environment is a professional open-office setting with collaborative work areas and shared resources. This is a full-time position with a minimum expectation of 40 hours per week.
Requirements
- At least 3 years of experience as a Data Engineer; professional services or large enterprise experience is ideal.
- Demonstrable expertise building data pipelines and cloud data solutions on Azure.
- Strong hands-on experience with Microsoft Azure data services, such as Data Factory, Synapse Analytics, Data Lake, and Databricks.
- Advanced SQL skills and experience with data modeling, transformation, and integration.
- Excellent communication skills and ability to translate technical solutions into business value.
- Ability to work independently and collaboratively in a fast-paced, client-facing environment.
- Comfort working across teams and explaining technical concepts to non-technical audiences.
- Proactive, resourceful, and adaptable approach, with a commitment to continuous improvement, automation, and reducing manual effort.
- Collaborative, service-oriented mindset and ability to work across teams.
- Strong analytical, organizational, and problem-solving abilities.
- High degree of empathy and customer orientation.
- Ability to meet deadlines, manage priorities, and deliver initiatives successfully.
- Ability to perform hand, wrist, and finger movements for 8 hours a day and sit for long periods.
Nice To Haves
- Bachelor's degree in computer science, Data Engineering, Information Systems, or a related field, or equivalent experience; the degree is preferred.
- Experience with Microsoft Fabric is strongly preferred.
- Knowledge of Python or other scripting languages.
- Familiarity with data governance, data quality, and compliance frameworks.
- Microsoft Azure data engineering or Microsoft Fabric certification.
- Experience in professional services or large enterprise environments.
Responsibilities
- Design, build, and maintain scalable data pipelines and integration workflows using Azure services such as Data Factory, Synapse Analytics, and Azure Databricks.
- Develop and maintain ETL/ELT processes for business reporting, analytics, and machine learning.
- Build ingestion patterns for business applications, APIs, relational databases, and file-based feeds.
- Implement scheduling, orchestration, automation, and error handling so recurring data loads run reliably with minimal manual intervention.
- Implement and support Microsoft Fabric solutions, including dataflows, lakehouses, data warehouses, and real-time analytics features.
- Organize OneLake data in layers that distinguish raw, enriched, and curated data and maintain traceability.
- Develop and maintain curated datasets and semantic models for Power BI reporting and self-service analysis.
- Monitor capacity, refresh schedules, and job performance, and tune performance as adoption and data volumes grow.
- Optimize cloud data architectures for performance, reliability, and cost efficiency.
- Apply dimensional modeling and other established modeling patterns to make data understandable, reusable, and consistent across reporting.
- Write and tune advanced SQL and Python or PySpark notebooks for complex transformations.
- Monitor, troubleshoot, and improve data workflows, addressing failures and performance bottlenecks at their source.
- Ensure data practices are high-quality, secure, and compliant with firm policy, client contractual obligations, and applicable data protection regulations.
- Implement data quality rules, validation, and monitoring to identify issues before they affect reporting or decisions.
- Apply access controls, sensitivity handling, and lineage practices in partnership with data governance resources.
- Collaborate with data architects, analysts, and business stakeholders to gather requirements and deliver solutions aligned with business goals.
- Support migration and modernization of legacy data systems into Azure and Microsoft Fabric environments.
- Explain technical options and trade-offs in terms business stakeholders can act on.
- Produce and maintain technical documentation for data pipelines, architecture, and engineering best practices.
- Follow source control and deployment practices, including Git-based development and structured promotion across environments.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
