Note: The job is a remote job and is open to candidates in USA. 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
Skills
- 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
Benefits
- Hybrid work arrangement
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