Cloud Engineer

Overview

ATI is Hiring! We are looking for a Cloud Engineer. As a Cloud Data Engineer, you will design, build, and maintain scalable data pipelines, systems and platforms with primary focus on Snowflake, and leveraging Microsoft Azure services to deliver integrated and high-performing data solutions. You will collaborate with business data analysts, data architects, data scientists, project managers, and GEHA’s business stakeholders to build solutions that ensure seamless data flow and enable actionable insights.

This role supports data development and maintenance efforts of the Data & Analytics activities and initiatives in alignment with the Enterprise Data strategy, policies, organizational goals, and governance policies. You’ll work in a cloud-native environment to design and optimize data solutions that improve performance, scalability, and efficiency.

• Proven experience as a Cloud Data Engineer or similar role, with a strong focus on Snowflake, including architecture, performance optimization and data modeling as well as hands-on experience with Azure cloud services.
• Advanced Snowflake ETL/ELT Development:
  Design and develop complex ETL/ELT pipelines natively in Snowflake using Snowflake streams, tasks, Snow Pipe and other features to automate data transformation and orchestration, leveraging Azure Data services and other tools where appropriate ensuring the efficient flow of data to multiple destinations for processing, storing, analysis, and delivery to downstream external consumers.
• Cloud Data Architecture:
  Design and implement Snowflake-based data solutions to support enterprise data platforms, integrating with Azure Data Lake Storage (ADLS), Azure SQL Data Warehouse, Azure Databricks to support data extracts, data sharing, business intelligence, analytics, and data science initiatives.
• Snowflake Data Architecture:
  Oversee the design and optimization of Snowflake architecture, including data models, schema design, partitioning, clustering, and query optimization to ensure high performance and low cost.
• Work independently on your assigned stories/tasks, work with other engineers & analysts on the team to take code all the way to Production using Change Management process.
• Participate in Architectural discussions, able to understand the bigger picture & expected to provide recommendation to make better architectural decisions for specific domains.
• Perform regular Code Reviews and making sure best practices are followed.
• Collaborate with Stakeholders:
  Work closely with cross-functional teams, including business data analysts, data architects, data scientists, project managers and business units, to define data requirements and implement data solutions that support business goals.
• Data Security, Governance & Compliance:
  Implement best practices to ensure data privacy, security, and compliance with relevant governance in the cloud environment.
• Automation and Monitoring:
  Implement and manage automated monitoring and logging for all data workflows and pipelines to ensure data integrity and operational reliability.
• Troubleshooting and Support:
  Troubleshoot issues with data pipelines, data integrity, and platform performance, providing timely resolutions to business-critical data needs.
• Ensure that all items follow company Change Management process.
• Participate in scrum, backlog grooming, refinement, planning and review sessions.
• Other duties as assigned.

• Requires at least 6-10 years of relevant technical or business work experience with demonstrated experience within healthcare industry or data and analytics.
• Bachelor’s degree in computer science, Information Technology, Data Engineering, Mathematics, or a related field or comparable experience.
• Expertise in designing and implementing data architectures on Snowflake including Snowpipe, Snowflake Tasks and Snowflake streams and Azure including Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Azure SQL Database, Azure Synapse, and Azure Databricks.
• Advanced experience with Snowflake data platform, including schema design, data sharing, internal & external marketplace, performance tuning, and cost…