Data Engineer / Analytics Consultant

As a Data Engineer / Analytics Consultant at McKee-Nix & Associates, you will be responsible for building and maintaining data infrastructure, pipelines, and analytics solutions that support business operations, sales strategy, and decision-making. You will work closely with cross-functional teams—such as sales, operations, and leadership—to translate data into insights that improve efficiency, forecasting, and growth across the company’s plumbing and mechanical distribution business. Key ResponsibilitiesDevelop, maintain, and optimize data pipelines (ETL / ELT) to integrate data from disparate systems (e.g., ERP, CRM, inventory, sales).Build and maintain data warehouses or data lakes for efficient storage and retrieval of structured and semi-structured data.Model data to support business reporting, analytics, and predictive insights (forecasting sales, inventory demand, etc.).Implement data transformation processes, standardize data definitions, and enforce data quality and validation rules.Create dashboards, reports, and visualizations for business stakeholders (sales leadership, operations, finance) to surface key metrics and trends.Collaborate with sales and operations teams to identify analytics needs, develop business intelligence solutions, and support data-driven decision-making.Monitor data pipeline performance, troubleshoot issues, and ensure reliability and scalability.Establish data governance practices, including documentation, lineage tracking, and data security standards.Train internal teams on data tools, dashboards, and analytics best practices.Stay current with industry trends, data tools, and best practices, and recommend improvements to architecture and data processes.RequirementsBachelor’s degree in Computer Science, Data Science, Information Systems, or a related field (or equivalent experience).3+ years of experience in data engineering, analytics, or a related role.Proficiency in SQL for data modeling and querying.Experience with data pipeline tools and frameworks (e.g., Python, Apache Airflow, or similar).Experience working with data storage technologies (data warehouses, lakes, cloud storage).Familiarity with BI / reporting tools (e.g., Power BI, Tableau, or similar).Strong problem-solving and analytical thinking skills, with the ability to interpret business needs into technical data requirements.Excellent communication skills, capable of bridging technical and non-technical stakeholders.Experience with data governance, documentation, and metadata management.BenefitsCompetitive base salary plus performance-based incentivesHealth, dental, and vision insurance401(k) retirement plan with company matchingGenerous paid time off: vacation, sick leave, and company holidaysFlexible work arrangements (hybrid or on-site, depending on business needs)Professional development support: training, certification reimbursement, and analytics conferencesTravel reimbursement for any on-site business visits or engagementsOpportunities for career advancement into senior analytics, data architecture, or leadership rolesWellness support: mental health resources, wellness stipend or gym benefitPaid parental / family leave