The Opportunity:Our client, a leading manufacturing organization based in Virginia, is seeking a skilled Data & Analytics Engineer to help design, build, and scale a modern enterprise data and analytics environment. This role will play an important part in establishing the organization's data foundation using Microsoft Fabric, Power Platform, Power BI, Tableau, and related cloud technologies.
This is an opportunity to take ownership of meaningful data initiatives and help shape how information is collected, integrated, governed, and used across the organization. You will work closely with business stakeholders and IT teams to build scalable data pipelines, reporting solutions, and analytics capabilities that improve visibility and enable better decision-making.
The ideal candidate combines strong data engineering capabilities with an understanding of business intelligence and enjoys translating complex data into reliable, accessible solutions. You will have the opportunity to contribute to enterprise-wide digital transformation while helping establish the standards, architecture, and tools that will support future analytics and AI capabilities.
What You'll Be Doing:- Design, build, and maintain a scalable enterprise data platform leveraging Microsoft Fabric, including OneLake, Data Factory, Data Engineering, Data Warehouse, Real-Time Analytics, and Lakehouse architecture.
- Develop and manage reliable data ingestion, transformation, and orchestration pipelines across multiple internal and external data sources.
- Design and implement ETL/ELT processes using Microsoft Fabric, Azure technologies, and modern data engineering practices.
- Integrate data from ERP, CRM, operational systems, cloud applications, APIs, and third-party platforms.
- Develop scalable data models, semantic models, and reusable data products that support enterprise reporting, analytics, AI, and operational decision-making.
- Build enterprise dashboards, scorecards, and analytical solutions using Power BI and Tableau.
- Create optimized datasets and semantic models that enable effective self-service analytics across the organization.
- Partner with stakeholders across Finance, Supply Chain, Manufacturing, Commercial, and other business functions to understand requirements and translate them into actionable data and analytics solutions.
- Help establish standardized KPIs, reporting definitions, and enterprise data standards.
- Monitor and optimize data pipelines, models, queries, and reporting solutions to improve performance, reliability, and scalability.
- Implement data quality, validation, metadata management, lineage, and master data practices.
- Establish and maintain appropriate data governance, role-based access, privacy, and security controls.
- Support audit, regulatory, and compliance requirements related to enterprise data.
- Leverage Power Platform, including Power Apps, Power Automate, and Dataverse, to support broader automation and business process initiatives.
- Apply Git/version control and CI/CD practices to support reliable and scalable development.
- Evaluate emerging technologies and capabilities across cloud analytics, data engineering, real-time analytics, and AI.
- Contribute to the organization's broader data and analytics roadmap while helping promote data literacy and modern data practices across the business.
What You'll Need to Be Successful:- Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, Statistics, or a related field; an equivalent combination of education and relevant experience may also be considered.
- 3-5 years of experience in data engineering, analytics engineering, business intelligence, or a related field.
- Experience designing, developing, and supporting production-level data pipelines and analytics solutions.
- Strong SQL capabilities, including experience with complex queries, views, stored procedures, transformations, and query optimization.
- Hands-on experience designing and maintaining ETL/ELT pipelines.
- Experience working with modern cloud data platforms such as Microsoft Fabric, Snowflake, Databricks, Azure Synapse, or similar technologies.
- Strong understanding of data warehousing, dimensional modeling, Lakehouse architecture, and modern data architecture principles.
- Experience developing dashboards and reporting solutions using Power BI, Tableau, or comparable business intelligence platforms.
- Experience with enterprise integrations, APIs, middleware, and data migration methodologies.
- Exposure to Microsoft Azure, AWS, or Google Cloud Platform.
- Understanding of data quality frameworks, monitoring, validation, metadata management, data governance, and master data practices.
- Knowledge of enterprise data security, privacy, access controls, and compliance considerations.
- Strong analytical and problem-solving skills with the ability to translate business requirements into practical technical solutions.
- Experience supporting analytics within Finance, Supply Chain, Manufacturing, Commercial, or similar business functions is considered an asset.
- Experience within manufacturing, distribution, industrial, private equity-backed, multi-site, or similarly complex organizations is preferred.
- Experience with Python, Spark, or PySpark is considered an asset.
- Exposure to Azure DevOps, CI/CD, DataOps, MLOps, real-time analytics, or streaming architectures is an asset.
- Experience integrating AI/ML capabilities within Microsoft Fabric or other modern data platforms is considered an asset.
- Microsoft certifications such as Fabric Analytics Engineer Associate, Power BI Data Analyst Associate, or Azure Data Engineer Associate are considered an asset.
Compensation Range: $90,000 - $110,000.
