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Data EngineerCharter Solutions • Minneapolis, Minnesota, United States
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Data Engineer

Charter Solutions
  • US
    Minneapolis, Minnesota, United States
  • US
    Minneapolis, Minnesota, United States
Apply Now

About

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.
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  • Minneapolis, Minnesota, United States

Languages

  • English
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