Data / Cloud Engineer

Are You Ready to Work for a Growing Company with a Great Culture?At Excel Services, Inc., we believe in helping people EXCEL. We are a growing Design-Build Mechanical, Electrical, Plumbing, and Low Voltage contractor focused on innovation, operational excellence, and building systems that perform better for our customers and our people.We are seeking a highly motivated and technically skilled Data / Cloud Engineer to join our growing Data, Analytics, & AI team. This individual will play a key role in designing, building, and optimizing the data platforms, cloud infrastructure, and AI-enablement systems that support business intelligence, automation, and strategic decision-making across the organization.If you enjoy solving complex technical problems, building scalable cloud solutions, and helping organizations unlock the power of data and AI, we want to hear from you.Position SummaryThe Data / Cloud Engineer builds, operates, and optimizes the data platform and pipelines that power the organization’s analytics, AI, and business operations. This role is responsible for turning architecture into working systems and trusted data — ensuring that ingestion, transformation, storage, and delivery of data are reliable, performant, secure, and cost-effective.This position partners closely with analytics, operations, finance, field leadership, and technology teams to create scalable and secure data solutions that improve operational visibility and accelerate business performance.Core ValuesTeamworkCollaborating to achieve shared success.IntegrityWe uphold honesty and respect consistently.InnovativeWe adapt to meet evolving demands.QualityWe deliver superior, lasting craftsmanship.AccountableWe take ownership of actions and results.LoyaltyWe are committed to our mission, employees, and community.Our MissionWe help people EXCEL.Essential Functions30% – Data Pipeline Development & IntegrationDesign, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data sources.Integrate cloud and on-premise systems into centralized data platforms.Build automated ingestion and transformation workflows to support analytics, reporting, and AI initiatives.Monitor pipeline performance and troubleshoot failures or bottlenecks.20% – Cloud Infrastructure & Data ArchitectureBuild and manage cloud-native infrastructure supporting data storage, processing, and orchestration.Assist in designing scalable, secure, and high-performing cloud architectures.Implement infrastructure-as-code and CI/CD deployment practices.Optimize cloud resource utilization and manage infrastructure costs.20% – Data Modeling & OptimizationDevelop and maintain performant data models and warehouse structures.Optimize query performance, storage efficiency, and data accessibility.Support business intelligence and dashboarding initiatives with clean and trusted datasets.Collaborate with stakeholders to translate business requirements into technical solutions.15% – Artificial Intelligence & Automation DevelopmentSupport AI and machine learning initiatives through feature pipelines and training dataset preparation.Assist in deploying and maintaining AI-enabled workflows and automation solutions.Contribute to intelligent process automation and predictive analytics initiatives.Partner with analytics and AI teams to operationalize machine learning capabilities.10% – Data Reliability & QualityImplement data quality validation, observability, and monitoring processes.Ensure data integrity, lineage, governance, and security compliance.Maintain role-based access controls (RBAC) and data access policies.Participate in incident response and root-cause analysis related to data reliability.5% – Other Duties as AssignedSupport additional initiatives and strategic technology projects as needed.Education, Training, and ExperienceMinimum QualificationsBachelor’s degree in Computer Science, Information Systems, Engineering, or a related field; or equivalent practical experience.3+ years of experience in data engineering, cloud infrastructure, or a closely related technical discipline.Proficiency with cloud platforms such as AWS, Azure, or GCP including compute, storage, networking, and managed data services.Hands-on experience building and maintaining ETL/ELT pipelines using tools such as dbt, Apache Spark, Airflow, or equivalent.Strong SQL skills and experience with cloud data warehouses such as Snowflake, BigQuery, Redshift, or Synapse.Experience with infrastructure-as-code tools such as Terraform or Pulumi and CI/CD practices.Familiarity with data governance, data quality frameworks, and RBAC implementation.Preferred QualificationsMaster’s degree in Business Analytics, Data Analytics, or similar field.Experience with machine learning feature pipelines, training dataset preparation, or inference pipeline support.Familiarity with real-time streaming frameworks such as Kafka, Kinesis, or Spark Streaming.Experience with data observability and lineage tools such as Monte Carlo, OpenLineage, or Atlan.Exposure to analytics or BI platforms such as Sigma, Tableau, or Power BI.Relevant cloud certifications including:AWS Solutions ArchitectGoogle Professional Data EngineerAzure Data EngineerCompensation & BenefitsCompetitive pay with paid overtimeMedical, dental, vision, life, and disability insurance401(k) retirement planPaid holidays and PTOPaid training and tuition reimbursementTeam incentive bonus programStrong culture focused on people and performance