Data Engineer Sr.

USA Donaldson Company•Bloomington, MN

1d•Hybrid

About The Position

Donaldson is committed to solving the world’s most complex filtration challenges. As an established technology and innovation leader, we are continuously evolving to meet the filtration needs of our changing world. Join a culture of collaboration and innovation that matters and a chance to learn, effect change, and make meaningful contributions at work and in communities. The Data Integration Engineer is responsible for designing, developing, and maintaining data integration solutions that enable trusted, scalable, and actionable data across the Mobile Solutions Americas (MSA) business. As a member of the MSA Business Insights team, this role will support the organization's vision to transform how we drive growth by embedding intelligence into every revenue decision and its mission to enable data-driven revenue decisions through actionable insights, scalable analytics, and trusted intelligence. This position reports directly within the MSA business organization and has a dotted-line relationship with the IT Manager responsible for Enterprise Data Engineering to ensure alignment with enterprise architecture, governance standards, security requirements, and best practices. Working closely with Data Scientists, Business/Data Analysts, and business stakeholders, the Data Integration Engineer will develop and maintain the data infrastructure, pipelines, and integrations that power business reporting, analytics, forecasting, and advanced data science initiatives. The role serves as a critical bridge between business needs and enterprise technology capabilities, ensuring that data is accessible, accurate, secure, and reliable. The technical domain of this position includes Snowflake Cloud Data Platform, Informatica Intelligent Cloud Services (IICS), enterprise application integrations, data replication, API management, and modern data engineering technologies. This is a highly collaborative, hands-on role that partners with Enterprise IT, Database Administrators, Infrastructure teams, Enterprise Architecture, and business stakeholders to deliver scalable data solutions that support growth and operational excellence. Qualified candidates must be able to work a hybrid schedule at our Bloomington office/facility.

Requirements

Bachelor's degree in Computer Science, Information Technology, Management Information Systems, Engineering, or related field.
5+ years of experience in Data Warehousing, Data Integration, or Data Engineering or equivalent combination for education and experience
Hands-on experience with one or more ETL/ELT platforms.
Experience with data analysis, requirements gathering, and data mapping for enterprise data solutions.
Experience with SQL development including Oracle SQL and PL/SQL.
U.S. Citizenship required.

Nice To Haves

Experience with Snowflake Data Cloud, Microsoft Azure, Amazon Web Services or similar cloud experience.
Experience with Data Management tools including Data Ingestion, Data Integration services, Data Transformation, Application Integration, and API Management tools.
Familiarity with Agile methodologies, SDLC processes, DevOps practices, CI/CD pipelines, and release management.
Familiarity with Unix/Linux environments.
Knowledge of relational and NoSQL databases, cloud storage platforms, identity management solutions, networking, and security technologies.
Strong understanding of data governance, metadata management, and data quality best practices.
Demonstrated ability to work effectively across business and technical teams.
Excellent written, verbal, and interpersonal communication skills.
Ability to manage multiple priorities and deliver results in a fast-paced environment.
Snowflake certification (SnowPro Core Certification or higher) preferred.
Ability to troubleshoot and resolve complex technical issues across integrated systems.

Responsibilities

Design, develop, and support data integration applications and infrastructure utilizing Informatica Intelligent Cloud Services and related technologies to process large volumes of enterprise data.
Build, optimize, and maintain scalable ETL/ELT pipelines that support analytics, reporting, and business intelligence initiatives.
Develop and maintain integrations between enterprise applications, databases, cloud platforms, and external data sources.
Create, test, troubleshoot, and optimize complex mapping tasks, task flows, and data movement processes to improve reliability and performance.
Support the ongoing evolution of the MSA analytics ecosystem by developing trusted and reusable data assets for business users.
Partner with Data Scientists and Business/Data Analysts to understand business requirements and translate them into scalable data solutions.
Enable advanced analytics, forecasting, reporting, and self-service business intelligence capabilities across the MSA organization.
Support revenue growth initiatives by ensuring timely, accurate, and accessible data for decision-making.
Participate in requirements gathering, data analysis, data mapping, and solution design activities with business stakeholders.
Administer and maintain Informatica Cloud services, Snowflake environments, and associated platform components.
Configure and manage agent servers, authentication protocols, encryption standards, system connections, and performance parameters.
Perform platform administration activities including user provisioning, security management, permissions, license management, and environment monitoring.
Provide Level 1 and Level 2 support for ETL/ELT processes and data platform operations, ensuring data availability and operational stability.
Partner with Enterprise Data Engineering and IT teams to ensure solutions align with enterprise standards, architecture principles, and governance requirements.
Design and implement secure data access controls and support compliance with Information Security Management policies and procedures.
Participate in metadata management, data quality initiatives, and data governance programs.
Contribute to architecture reviews, code reviews, and design reviews to ensure solutions are supportable, maintainable, and scalable.
Participate in proof-of-concept activities for emerging technologies, analytics capabilities, and data management solutions.
Evaluate new tools and technologies that improve integration, automation, analytics, and data management capabilities.
Recommend and implement process improvements that enhance data quality, operational efficiency, and platform performance.