Senior Data Engineer

• Designs, builds, and maintains scalable data pipelines and data architecture, including ELT/ETL processes across multiple data sources.
• Develops and publishes curated datasets and data products for analytics, reporting, machine learning, and application use cases.
• Administers and optimizes Snowflake environments, including database objects, warehouses, and role-based access controls.
• Implements and enforces data governance practices such as data quality validation, metadata management, lineage tracking, and access policies.
• Collaborates with business and technical stakeholders to gather requirements, troubleshoot issues, and deliver data solutions.
• Monitors platform performance and resource utilization, implementing optimizations to balance cost and efficiency.
• Supports onboarding of new data sources and integration of enterprise systems into the data platform.
• Leads data incident response, root cause analysis, and remediation for pipeline or data quality issues.
• Maintains documentation for data architecture, pipelines, governance policies, and standards.

**Must be willing to work onsite in Duluth 5 days a week, can work an earlier shift (7-4PM if needed) Target Salary - 130-150k

• Bachelor’s degree in Computer Science, Engineering, or related field
• 6 - 8 years of experience in data engineering or related field
• Strong experience designing and maintaining production-grade data pipelines in cloud environments
• Advanced proficiency in SQL and query optimization
• Proficiency in Python for data processing and automation
• Experience with Snowflake platform administration and performance tuning
• Experience with data engineering tools such as Apache Spark, Airflow, dbt, or similar
• Strong understanding of data modeling (dimensional modeling, schema design)
• Experience implementing data governance (RBAC, data quality, lineage, metadata)
• Familiarity with CI/CD practices and version control tools (Git)
• Strong analytical, problem-solving, and troubleshooting skills
• Excellent communication skills with ability to translate technical concepts to business stakeholders
• Bachelor’s degree in Computer Science, Engineering, or related field
• 6 - 8 years of experience in data engineering or related field
• Strong experience designing and maintaining production-grade data pipelines in cloud environments
• Advanced proficiency in SQL and query optimization
• Proficiency in Python for data processing and automation
• Experience with Snowflake platform administration and performance tuning
• Experience with data engineering tools such as Apache Spark, Airflow, dbt, or similar
• Strong understanding of data modeling (dimensional modeling, schema design)
• Experience implementing data governance (RBAC, data quality, lineage, metadata)
• Familiarity with CI/CD practices and version control tools (Git)
• Strong analytical, problem-solving, and troubleshooting skills
• Excellent communication skills with ability to translate technical concepts to business stakeholders
• Bachelor’s degree in Computer Science, Engineering, or related field
• 6 - 8 years of experience in data engineering or related field
• Strong experience designing and maintaining production-grade data pipelines in cloud environments
• Advanced proficiency in SQL and query optimization
• Proficiency in Python for data processing and automation
• Experience with Snowflake platform administration and performance tuning
• Experience with data engineering tools such as Apache Spark, Airflow, dbt, or similar
• Strong understanding of data modeling (dimensional modeling, schema design)
• Experience implementing data governance (RBAC, data quality, lineage, metadata)
• Familiarity with CI/CD practices and version control tools (Git)
• Strong analytical, problem-solving, and troubleshooting skills
• Excellent communication skills with ability to translate technical concepts to business stakeholders
• Experience with Medallion architecture (Bronze/Silver/Gold layers)
• Experience supporting BI tools (Power BI, Tableau) and ML/AI pipelines
• Experience integrating ERP, transactional, and third-party data sources
• Exposure to data mesh, data contract, or data product frameworks.