phData
Principal Solution Architect
US - Remote · Principal
Sponsorship not specifiedDetected 28 days ago
PythonGitSQLNoSQLCassandraSnowflakeRedshiftDatabricksAWSGCPAzureCloud PlatformsTerraformCI/CDKafkaSparkAirflowdbtLeadershipCommunicationCollaborationMentoringPublic Speaking
About the role
- We are looking for a Principal Solutions Architect - Managed Services to join our Managed Services team.
Responsibilities
- Own and drive the design, provisioning, and enhancement of cloud-native data solutions on AWS and/or Azure, leveraging deep expertise in Snowflake and related data services for enterprise-scale platforms.
- Lead the operation and management of modern data platforms-from streaming and data lakes to analytics-across a progressively evolving technical stack for multiple concurrent customer accounts.
- Provide architectural and operational guidance for cloud-native data warehouses (e.g., Snowflake, Redshift) and distributed storage technologies (e.g., S3, ADLS, NoSQL) to support large user bases.
- Recommend appropriate technologies and approaches to ensure performance, security, scalability, and user satisfaction, including data model design for data warehouses and data lakes.
- Collaborate across technology stacks and organizational silos to integrate disparate functions and technologies into cohesive solutions.
- Create and deliver detailed technical presentations and recommendations for executive and senior stakeholders, articulating complex concepts clearly and confidently.
Requirements
- 15+ years of experience architecting, operating, and optimizing modern cloud-based data platforms and data warehouses in enterprise environments.
- Advanced data platform expertise in Snowflake and at least one major cloud platform (AWS and/or Azure), with experience in Databricks or similar technologies.
- Hands-on experience with cloud and distributed data storage technologies such as S3, ADLS, Cassandra, or other NoSQL systems.
- Production experience with workflow management and orchestration tools such as Airflow, AWS Managed Airflow, and Luigi.
- Extensive experience with Infrastructure as Code using Terraform or CloudFormation.
- Familiarity with CI/CD and deployment frameworks, including tools like Bitbucket, GitHub, Flyway, and Liquibase.
- Ability to describe specific engineering tasks completed with AI assistance.
- Experience delivering projects and managed services for external or internal clients in a professional services, consulting, or complex enterprise environment.
Nice to have
- Snowflake SnowPro Core certification.
- One or more Snowflake advanced certifications.
- Bachelor's degree in Computer Science or a related field.
- Contributions to open source, technical communities, speaking, writing, or internal accelerators are a plus.
- This role is based in US and operates primarily in Central and/or Eastern time zones with significant overlap to US Central Time.
- Some flexibility may be required to collaborate across time zones with colleagues and clients.
- Growth Opportunities: Access to challenging projects, mentorship, and structured development pathways.
- Values-Driven: We prioritize doing the right thing for our clients, our teams, and our community.
Benefits
- Delegate work effectively, coach engineers, and mentor team members, fostering upskilling and continuous learning across evolving technology stacks.
Company info
- Work with a supportive, high-performing global team that values transparency, autonomy, and continuous improvement.
- Translate business and technical requirements into Epics, Stories, and Tasks that mature and improve customers' data platforms, ensuring timely and successful delivery of these initiatives.
- Continually identify and deliver automation and optimization opportunities that expand and harden customers' data platforms and phData's managed services offerings.
- Manage the human side of delivery, engaging respectfully and confidently with teammates and customers, including during challenging conversations.
This listing is sourced directly from phData's careers page and normalized into a canonical job model.