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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer III - **Company:** Hard Rock Hotel and Casino - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Business Systems, Cloud Computing, Cloud Database, Cloud Engineering, Cluster Analysis, Continuous Delivery, Data Architecture, Data Validation, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Security, Data Sharing, Data Systems, Data Warehousing, Dimensional Modeling, Distributed Data Store, Github, Identity and Access Management, Python (Programming Language), Meta-Data Management, Performance Tuning, Software Architecture, Role-Based Access Control, Software Engineering, Workflow Management Systems, Enterprise Data Management, Cloud Platform System, Azure Data Factory, Snowflake, Apache Spark, Git, Data Lakes, Data Lineage, Software Version Control, Data Pipelines, Serverless Computing, Databricks - **Published:** August 30, 2026 - **Apply:** https://www.jobmonkeyjobs.com/career/27974799/Data-Engineer-Iii-Any-All-Cities-984 ## About the Role * 7+ years of professional experience in Data Engineering, Data Warehousing, or related disciplines * 5+ years of hands-on experience with Snowflake in enterprise environments * Proven expertise designing, developing, and supporting large-scale data platforms and modern analytics architectures * Experience working in cloud-based environments and supporting mission-critical business systems, * 7+ years of professional Data Engineering experience * 5+ years of hands-on Snowflake experience in enterprise environments * Strong expertise with: + Snowflake SQL + Tasks + Streams + Virtual Warehouses + RBAC + Clustering + Performance Optimization * Advanced SQL development skills * Strong experience building modern ETL/ELT data pipelines * Experience with cloud platforms such as Azure and/or AWS * Proficiency in Python for data engineering and automation * Experience with orchestration tools including: + Azure Data Factory (ADF) + Apache Airflow * Strong understanding of: + Data Modeling + Data Warehousing + Distributed Data Systems + Data Integration Architectures * Proven ability to independently own solutions from requirements gathering through deployment and support * Excellent communication, collaboration, and stakeholder management skills Preferred Qualifications * Experience implementing CI/CD pipelines for data engineering workloads * Experience with: + Azure DevOps + GitHub Actions + Git-based source control practices * Knowledge of modern big data frameworks including: + Databricks + Apache Spark + Delta Lake * Experience supporting high-volume enterprise data platforms with strict performance and availability requirements * Experience implementing: + Data Governance Frameworks + Metadata Management Solutions + Data Quality Programs + Data Lineage Initiatives * SnowPro Certification(s) preferred * Familiarity with data security, compliance, and access management best practices Leadership & Communication * Strong written and verbal communication skills. * Ability to document technical designs, data architectures, and operational procedures. * Comfortable interacting with technical teams, business leaders, and executive stakeholders. * Demonstrated ability to mentor junior engineers and share best practices across teams. * Ability to influence architectural decisions and drive continuous improvement initiatives. Soft Skills & Competencies * Strong problem-solving and analytical abilities. * Ability to translate ambiguous or evolving requirements into scalable technical solutions. * Strong attention to detail and commitment to data quality. * Collaborative, team-oriented mindset with a passion for continuous learning. * High degree of ownership, accountability, and professionalism. * Ability to manage multiple priorities in a fast-paced environment. ## Description We are seeking a highly skilled Senior Snowflake Data Engineer to design, develop, and optimize enterprise data solutions that support analytics, reporting, and business intelligence initiatives across the organization. This role will be responsible for building scalable data pipelines, implementing Snowflake best practices, and ensuring the reliability, performance, and security of critical data assets. The ideal candidate is a hands-on data engineering professional with deep expertise in Snowflake, cloud-based data platforms, and modern ELT/ETL architectures. This individual will collaborate closely with business stakeholders, data analysts, data scientists, and application development teams to deliver scalable and high-performing data solutions that enable data-driven decision-making., Data Engineering & Pipeline Development * Design, develop, and maintain scalable, high-performance data pipelines and ELT/ETL processes utilizing Snowflake and modern data engineering frameworks. * Build and support enterprise Data Lakes and Data Warehouses. * Develop robust data integration solutions that ensure data quality, consistency, and reliability. * Optimize data movement, transformations, and processing workflows across multiple systems and platforms. * Implement automated and reusable data engineering patterns to improve efficiency and maintainability. Snowflake Platform Engineering * Architect, develop, and maintain Snowflake-based data solutions. * Design and optimize Snowflake data models to support analytics, reporting, and operational workloads. * Configure and manage Snowflake Tasks, Streams, Virtual Warehouses, RBAC, and data-sharing capabilities. * Monitor and optimize Snowflake performance, storage utilization, and query efficiency. * Implement cost optimization strategies to maximize platform value while maintaining performance standards. Key Snowflake Technologies: * Snowflake SQL * Streams * Tasks * Virtual Warehouses * Role-Based Access Control (RBAC) * Data Sharing * Clustering Keys * Performance Tuning * Cost Optimization Data Architecture & Modeling * Design scalable and maintainable data models that support business intelligence, analytics, and operational reporting requirements. * Apply dimensional modeling and data warehousing best practices. * Establish standards and governance frameworks for enterprise data assets. * Contribute to long-term data architecture strategy and platform evolution. Cloud Data Solutions * Build and support cloud-based data platforms leveraging Azure and/or AWS. * Integrate cloud-native services into enterprise data workflows. * Collaborate with cloud engineering teams to ensure scalability, security, and reliability of data environments. * Optimize cloud resource utilization and operational costs. Data Quality & Reliability * Monitor the health and performance of data pipelines and platform services. * Troubleshoot and resolve issues related to data accuracy, completeness, latency, and reliability. * Implement data validation, testing, and monitoring processes. * Support root cause analysis and continuous improvement initiatives. Collaboration & Stakeholder Engagement * Partner with data analysts, data scientists, product owners, and business stakeholders to translate business requirements into effective technical solutions. * Participate in architectural discussions and contribute to technology decisions and development standards. * Communicate technical concepts effectively to both technical and non-technical audiences. * Support cross-functional initiatives focused on advancing enterprise data capabilities. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [What’s the Difference between a Junior, Mid, and Senior Developer?](https://www.wearedevelopers.com/magazine/238-what-s-the-difference-between-a-junior-mid-and-senior-developer) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again)