Data Engineer III

Our team members are the key to our company’s success, and their health and well-being, as well as that of their families, is very important to us. We offer a comprehensive benefits package that allows our team members stay healthy, plan for their future and maintain a healthy work-life balance. Benefits may vary with employment status.  To see our fill list of Team Member Benefits please visit our career site: www.gotoworkhappy.com/benefits

Job 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.

Required Experience

• 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

Key Responsibilities

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.

Required Qualifications

• 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.