Data Engineer III

Hard Rock International is seeking a data engineering professional to support enterprise analytics, reporting, and business intelligence initiatives. The role designs and optimizes Snowflake-based data platforms, pipelines, architectures, and cloud data solutions while ensuring data quality, reliability, security, and performance. It also collaborates with technical teams and business stakeholders to deliver scalable, data-driven solutions.

Responsibilities:

• 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
• 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
• 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
• 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
• 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
• 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

Requirements:

• 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
• 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
• 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
• 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