Data Engineer

Charter Solutions is hiring a Data Engineer locally in the Minneapolis area.

Key Responsibilities

• Lead the strategy, architecture, and evolution of the enterprise data platform, overseeing data ingestion, transformation, storage, and delivery capabilities.
• Design, develop, and maintain scalable data pipelines and data models within Snowflake and AWS environments, remaining actively engaged in hands-on engineering work.
• Establish and enforce best practices for data architecture, modeling, quality assurance, testing, lineage, metadata management, and governance.
• Develop and support reliable integrations with internal applications and third-party platforms, including sources such as Piano, Sailthru, GraphQL APIs, and other data providers.
• Ensure data is accurate, accessible, and optimized to support analytics, business intelligence, and reporting initiatives across Snowflake, Domo, and related platforms.
• Implement monitoring, observability, and alerting solutions to proactively identify and resolve data pipeline issues while improving platform reliability and performance.
• Provide technical leadership, mentorship, and guidance to data engineering team members, promoting engineering excellence and continuous improvement.

Qualifications

• Proven experience designing, building, and supporting enterprise-scale data platforms and production data pipelines.
• Advanced expertise in Snowflake, SQL, and data modeling, with a strong understanding of data warehousing and analytics architecture principles.
• Hands-on experience with AWS cloud services, workflow orchestration tools, and modern ELT/ETL and data transformation frameworks.
• Demonstrated ability to establish technical direction, drive platform strategy, and influence data architecture decisions while remaining an active contributor.
• Experience implementing data quality, governance, observability, and operational best practices within modern data ecosystems.
• Familiarity with AI-assisted development tools and the ability to effectively evaluate, validate, and apply AI-generated outputs in engineering workflows.
• Strong collaboration and communication skills, with the ability to partner across engineering, analytics, and business teams to deliver scalable data solutions.