• Design, build, and maintain scalable cloud‑native data pipelines supporting batch and near‑real‑time use cases. • Engineer and optimize data ingestion, transformation, and orchestration pipelines using Azure Data Factory, Microsoft Fabric, Databricks, and related services. • Implement and maintain lakehouse and medallion architectures (bronze, silver, gold) to support analytics and AI workloads. • Develop robust transformation logic using SQL, PySpark, and Python with a focus on performance and maintainability. • Partner with Analytics/BI Engineers to ensure datasets are optimized for semantic layers and AI consumption. • Collaborate with data scientists to support feature engineering and model training workloads. • Implement data quality, validation, lineage, and observability solutions to ensure trust in data assets. • Design and enforce data security practices including access controls, encryption, and data classification. • Automate deployment and operations using DataOps and infrastructure‑as‑code practices. • Create and maintain technical documentation, runbooks, and architecture diagrams. • Provide technical leadership and mentorship to junior data engineers.

Role Description POWTEC Solutions is hiring a Data Analyst to support a federal client engagement with NOAA’s Office of the Chief Administrative Officer (OCAO). In this role, you will work with enterprise facility management systems to ensure data integrity, build meaningful dashboards, and help drive informed decisions about federal real property investments. This is a full-time, salaried contract position expected to run approximately 8 months, with the potential for extension. You will work largely independently and remotely, with a preference for candidates located on the East Coast — ideally in the Silver Spring, MD or Tampa Bay, FL areas. What You’ll Do - Data Quality & System Integration - Perform quality assurance on Facility Condition Assessment (FCA) data across enterprise platforms, including BUILDER SMS and Archibus. - Review facility records for completeness, accuracy, and consistency, and reconcile data across systems. - Identify anomalies and gaps, then document findings with recommended corrective actions. - Data Mining & Analysis - Extract and preprocess data from multiple sources across the facility portfolio. - Evaluate data quality, remove duplicates and inconsistencies, and apply statistical methods to surface meaningful insights. - Use machine learning techniques where applicable to support deeper analysis. - Dashboard Development & Reporting - Build and maintain interactive dashboards and KPI reports using Tableau or Power BI. - Develop clear data visualizations and written summaries that translate complex findings into actionable insights for government decision-makers. - Data Governance & Documentation - Help establish data governance policies and standards. - Create data dictionaries, user manuals, and training materials. - Develop and maintain a Data Refresh and Sustainment Guide, including ETL processes and update schedules. Qualifications - Experience with data analysis, quality assurance, or business intelligence work. - Proficiency with at least one BI tool (Tableau or Power BI strongly preferred). - Comfort working with enterprise data platforms and large, multi-system datasets. - Strong attention to detail and ability to document findings clearly. - Ability to work independently with minimal day-to-day supervision. Requirements - Familiarity with facility management or real property systems (Archibus, BUILDER SMS, or similar). - Experience supporting federal or government contractor environments. - Knowledge of ETL processes and data governance practices. Work Environment - Location: Remote; East Coast strongly preferred (Silver Spring, MD or Tampa Bay, FL area). - Schedule: Full-time, salaried. - Contract Duration: Approximately 8 months, with potential for extension. - Compensation: Approximately $40/hour equivalent, commensurate with experience. - Clearance: No security clearance required; candidate must be able to pass a federal background investigation and obtain a CAC and NOAA email address. - Tools: Work is performed in a Government-furnished Google Workspace environment using Government-issued accounts and multi-factor authentication.

Role Description The Senior Data Analyst acts as a strategic partner to business functions across ANBL, understanding and anticipating their needs and translating them into actionable insights through reports, dashboards, KPIs, and supporting semantic models. As a primary point of contact for the business, the role works closely with stakeholders to shape and guide analytical solutions, advise on underlying data requirements, and ensure high-quality, scalable outputs through validation, functional testing, and UAT. This role promotes data literacy across the organization, enables data-driven decision-making at both operational and strategic levels, and mentors team members while contributing to the continuous improvement of analytics practices. Additional Responsibilities - Requirements Identification: Partner with business stakeholders to understand and anticipate needs, translating them into scalable analytical solutions while advising on approaches that best support strategic objectives. - Modeling, Analysis & Insights: Design, maintain, and optimize semantic models, perform advanced analysis (e.g., forecasting, segmentation, trend analysis), and deliver insights that uncover drivers, risks, and opportunities to inform business strategy. - Decision Support: Partner with business users and leaders to translate insights into actionable recommendations and initiatives that support strategic and operational decision-making. - Stakeholder Engagement: Build and maintain strategic relationships across ANBL to anticipate evolving business needs and influence the delivery of high-value analytics solutions. - Data Quality Assurance: Proactively monitor and validate data quality, collaborating with Data Governance and Data Solution Developers to address systemic issues and improve data reliability. - Documentation: Establish and maintain documentation standards to support knowledge sharing, solution maintainability, and broader data literacy across the organization. - Continuous Improvement: Lead the review of existing processes to identify and implement more efficient ways of working that deliver increased value to the organization. - Personal & Organizational Capability Building: Promote data literacy across the organization and mentor team members through coaching and knowledge sharing, while advancing expertise in evolving tools, technologies, and industry practices. Qualifications - Post‑secondary degree in Computer Science, Information Systems, Mathematics, Finance, Business Administration, or a related field. - 5+ years of experience in data analysis, report development, and data modeling. - Ability to lead the identification, interpretation, and refinement of complex business requirements, translating them into scalable analytical and reporting solutions aligned with strategic objectives. - Proven experience designing and delivering enterprise Power BI reports and semantic models using Fabric Lakehouse or comparable cloud-based data platforms. - Ability to communicate complex insights effectively through data storytelling and visualization, applying and promoting data visualization and dashboard design best practices. - Advanced proficiency in SQL, DAX, and Power Query (M), with the ability to develop performant and scalable analytical solutions. - Strong analytical and problem-solving capabilities, with the ability to interpret complex datasets and identify key drivers, trends, and opportunities. - Strong communication and interpersonal skills, with the ability to influence and collaborate with stakeholders across technical and business teams. Requirements - Technical Stack: - Microsoft Fabric - Power BI (reports, dashboards, semantic models) - Power BI Service (workspaces, deployment workflows, Git integration) - SQL, DAX, Power Query (M) - Microsoft Excel, Forms, Power Automate, SharePoint - Would be an asset if you had: - Exposure to Microsoft Fabric Lakehouse architecture and medallion (bronze, silver, gold) design patterns. - Familiarity with data warehousing concepts and dimensional modeling approaches. - Experience with Microsoft Dynamics 365 or similar ERP/CRM systems. - Exposure to data governance concepts, including data lineage, metadata management, and data cataloging. - Microsoft Certified: Power BI Data Analyst Associate (PL-300). Benefits - Comprehensive benefits package, including medical, dental coverage and a generous pension plan. - Access to a Health Spending Account or Wellness Subsidy. - Opportunities to utilize flexible work arrangements, such as remote or hybrid work. Company Description Alcool NB Liquor (ANBL) is a provincial Crown corporation responsible for the purchase, importation, distribution, and retail activity for all beverage alcohol in the province. Our sister company, Cannabis NB (CNB), manages retail cannabis sales for the province, providing safe and legal products while focusing on education, safety and responsible access. Together, ANBL & CNB return 100% of profits to the Government of New Brunswick to benefit all New Brunswickers while responsibly serving customer and communities across the province. At ANBL, we take our social responsibility seriously. With our Corporate Social Responsibility Strategy to guide us, we are committed to: - Responsible selling through our CHECK 30 program, which specifies that customers who look younger than 30 will be asked for valid photo identification. - Food security through our partnership with Feed Nourrir NB to help get more food to the New Brunswickers who need it. - Helping New Brunswickers get home safely through our Safe Ride program, providing FREE transportation at ANBL-sponsored events.

• Collect, manage, clean, enrich, and explore vast datasets to unlock actionable intelligence. • Transform Business Questions into Insight. • Translate complex business problems into structured analysis. • Design and deliver compelling visual stories using modern BI and data visualisation tools. • Present findings clearly to both technical and non-technical stakeholders. • Build low-latency data pipelines and streaming analytics solutions. • Develop automated queries, dashboards, and SaaS-embedded analytics. • Prepare curated, high-quality datasets for ML training and inference. • Support feature stores, model outputs, and data versioning. • Integrate with ML platforms and apply MLOps best practices such as A/B testing and model monitoring. • Create interactive live dashboards using leading BI platforms. • Implement robust governance frameworks covering naming standards, lineage, classification, and retention. • Design automated validation, anomaly detection, and monitoring systems. • Partner closely with Product, Engineering, DevOps, and Data teams to align analytics with evolving product strategies.