Senior Data Engineer (Contract)

Location: Chanhassen, MN — Hybrid (3 days onsite per week)

Position Overview

We are seeking a Senior Data Engineer to join an Enterprise BI & Data team and build scalable, trusted data products that enable operational reporting, financial analysis, member personalization, and advanced analytics.

This is an analytics-engineering-focused position for a hands-on mid-to-senior-level data professional—not a lead architect role. Snowflake is a core platform and central skill for this position. The ideal candidate has significant hands-on experience designing, developing, optimizing, and supporting Snowflake-based data solutions; advanced SQL expertise; strong data modeling and ELT development skills; and the ability to partner effectively with business stakeholders, architects, analysts, and software engineering teams.

Responsibilities

• Design, develop, and deliver reliable data engineering and analytics engineering solutions for enterprise data initiatives, with Snowflake as the primary cloud data platform.

• Build, maintain, and optimize scalable Snowflake data pipelines that ingest, transform, validate, and publish structured and unstructured data.

• Develop high-quality, performant SQL transformations, views, stored procedures, and data models in Snowflake to support reporting, analytics, and self-service BI.

• Design and maintain Snowflake database, schema, table, and data-model structures that enable governed, scalable, and analytics-ready data consumption.

• Monitor and improve Snowflake query performance, warehouse utilization, workload efficiency, and overall platform cost performance.

• Partner with solution architects, business partners, data analysts, and engineering teams to translate business needs into durable data solutions.

• Collaborate on domain-oriented data modeling and modern data architecture practices.

• Improve data quality, observability, documentation, lineage, security, and maintainability across the data platform.

• Participate in peer code reviews, solution design reviews, testing, and technical troubleshooting.

• Investigate and resolve data pipeline, Snowflake platform, data quality, and performance issues.

• Contribute to Agile ceremonies, including sprint planning, backlog refinement, standups, and retrospectives.

• Help establish and apply reusable Snowflake engineering patterns, data standards, and best practices in partnership with technical leadership.

Required Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field; equivalent relevant experience will also be considered.

• 4+ years of experience designing and developing data warehouse, analytics, or data engineering solutions.

• 3+ years of hands-on Snowflake experience in a production environment.

• Advanced SQL skills, including developing complex transformations, performance-tuning queries, and supporting analytics workloads in Snowflake.

• Experience designing and maintaining Snowflake data models, including dimensional, domain-oriented, or analytics-ready models for self-service reporting and BI.

• Experience developing and supporting Snowflake ELT/ETL workflows, including data ingestion, transformation, validation, and publishing processes.

• Knowledge of Snowflake performance and cost-management concepts, including virtual warehouses, query optimization, workload management, and storage considerations.

• Strong experience building ELT/ETL pipelines using Python, SQL, and/or modern orchestration and transformation tooling.

• Working knowledge of relational databases, data warehousing concepts, and modern data architecture principles.

• Experience collaborating on an Agile/Scrum delivery team.

• Ability to communicate clearly with both technical teams and business stakeholders.

• Demonstrated ability to independently troubleshoot complex Snowflake, data pipeline, data quality, and performance issues.

Preferred Qualifications

• Experience with Snowflake capabilities such as Snowpipe, Streams, Tasks, dynamic tables, secure data sharing, and role-based access controls.

• Experience with modern transformation and analytics engineering tools such as dbt, including dbt-Snowflake.

• Experience with Snowflake administration, governance, security, metadata management, or data cataloging practices.

• Experience with Azure data services, including Azure Data Factory, Azure SQL, Azure Data Lake, or related technologies.

• Familiarity with CI/CD practices and tools such as GitHub, Azure DevOps Pipelines, or similar platforms.

• Experience with NoSQL technologies, such as Azure Cosmos DB.

• Experience supporting real-time or streaming data workloads using Kafka, Azure Event Hubs, or Azure Service Bus.

• Familiarity with data lake and lakehouse concepts and technologies.

• Relevant cloud, Snowflake, or data engineering certifications, such as SnowPro Core, Microsoft Azure Data Engineer Associate, or Azure Data Fundamentals.