Senior Data Engineer

GlobalSource specializes in IT contract and direct-hire recruiting, but enough about us! You're here to learn about our client. They are an Appleton-based software company specializing in tax compliance technology, backed by a well-established Wisconsin organization. They're investing in their data and analytics capabilities and seeking a Senior Data Engineer to help build their data infrastructure, support emerging AI initiatives, and play a key role in a growing team.

See below for details, or contact Heidi at [email protected] to learn more!

Senior Data Engineer

Full-time | Remote

NO C2C | USC or GC Holder only

Summary

We're seeking a Senior Data Engineer to play a key role in building and shaping a growing enterprise data and analytics practice. This is an opportunity to join a small, highly visible team where you'll have significant ownership, influence technical direction, and help establish the data foundation supporting business intelligence, advanced analytics, and AI initiatives.

This isn't a traditional data engineering role focused solely on pipelines or ingestion. We're looking for someone with deep data engineering expertise who enjoys working across the full data lifecycle, from understanding business requirements and designing architecture to building pipelines, transforming data, implementing governance, and delivering solutions.

You'll serve as a technical leader within a modern Snowflake and Microsoft Azure environment, working closely with the Director of Data & Analytics and cross-functional stakeholders. The ideal candidate is hands-on, technically strong, adaptable, and excited about building something rather than maintaining an established environment.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and infrastructure using Snowflake, Microsoft Azure, and modern data engineering tools.
• Own end-to-end data engineering initiatives, including requirements gathering, architecture, ingestion, transformation, modeling, governance, and delivery.
• Architect data integration solutions across operational databases, SaaS applications, external sources, and enterprise systems using batch, streaming, and change data capture (CDC) patterns.
• Build and maintain transformation frameworks using dbt or comparable technologies, establishing standards for data quality, testing, documentation, and maintainability.
• Develop and optimize SQL queries, data models, and Snowflake workloads for performance, scalability, and cost efficiency.
• Establish data engineering best practices around CI/CD, version control, orchestration, observability, pipeline reliability, and incident response.
• Support data governance initiatives, including metadata management, data lineage, schema management, security, and regulatory compliance.
• Partner with business stakeholders to translate requirements into technical solutions, supporting reporting, analytics, Power BI, and downstream applications.
• Help build the data foundation for emerging AI capabilities, including AI-assisted analytics, regulatory intelligence, and agent-based workflows.
• Collaborate with leadership on technical strategy, platform improvements, and the development of a scalable data and analytics practice.
• Mentor fellow engineers and contribute to the team's technical standards and capabilities.

Required Qualifications

• 4–7+ years of professional data engineering experience, including hands-on ownership of production data platforms and complex data pipelines.
• Strong Snowflake experience, including data warehouse design, performance tuning, access controls, and cost optimization.
• Strong experience with Microsoft Azure data services, including Azure Data Factory, Azure SQL, Azure Storage, and related cloud infrastructure.
• Advanced SQL skills, including complex queries, performance optimization, data modeling, and schema design.
• Experience with modern data transformation tools such as dbt, Dataform, or equivalent frameworks.
• Experience with workflow orchestration tools such as Azure Data Factory, Airflow, or Dagster.
• Proficiency in Python, Scala, or another programming language used for data engineering and integration.
• Strong understanding of ETL/ELT, data ingestion, dimensional modeling, data warehousing, and modern data architecture.
• Experience implementing CI/CD, automated testing, data quality monitoring, and production pipeline support.
• Working knowledge of data governance, lineage, metadata management, and security practices.
• Experience using AI-assisted development tools such as GitHub Copilot, Claude, or comparable technologies.
• Strong communication skills and demonstrated ability to work directly with business stakeholders, translate requirements, and independently drive projects through completion.
• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline, or equivalent experience.

Preferred Qualifications

• Snowflake or Microsoft Azure certifications.
• Experience with Power BI, including semantic models, datasets, and reporting integrations.
• Experience with AI/ML integrations, Azure OpenAI, Azure AI Foundry, or AI agents.
• Familiarity with streaming technologies such as Kafka or Azure Event Hubs.
• Experience with infrastructure-as-code tools such as Terraform or Bicep.
• Exposure to regulated environments, SOC 2 compliance, or sensitive-data governance.
• Experience establishing data engineering standards or contributing to a Data & Analytics Center of Excellence.

Work Arrangement: Onsite, hybrid, and remote candidates will be considered. Final candidates must be available for an onsite interview in Appleton, Wisconsin.