Data Engineer (Chicago-Based - Onsite/Hybrid)

HNI Corporationis a global family of brands for the workplace and home dedicated to enhancing the spaces where we live, work, and gather. Wepride ourselves on fostering an environment where we make a positive impact on others; upholding our beliefs in integrity, inclusion and belonging.

Position Summary:

The Data Engineer is an early-career technology professional responsible for developing, maintaining, and supporting the data pipelines and data structures that enable analytics, reporting, and data-driven decision-making across HNI Corporation.

Working as part of the Data Engineering and Decision Sciences organization, this position helps move data from enterprise applications and other source systems into HNI's cloud-based data environment, where it can be organized, transformed, and made available to Business Intelligence, analytics, and other data consumers.

The Data Engineer I performs hands-on development using SQL, Python, ETL/ELT technologies, and cloud data platforms, with an emphasis on Microsoft Azure and Snowflake. The role works within established data architecture, engineering standards, security requirements, and development practices while gradually building the technical depth necessary to design increasingly complex data solutions.

This position is appropriate for someone with foundational professional experience in data engineering, database development, business intelligence, software development, or a related technical discipline who is ready to expand their experience working with enterprise-scale data. Success requires strong analytical and problem-solving abilities, attention to data quality, curiosity about how data is created and used, and a willingness to learn new technologies and engineering practices.

Ideal Candidate Profile:

The ideal candidate has already moved beyond learning SQL and programming solely in an academic environment and has begun applying those skills to real business data and production technology environments. They may currently be a junior Data Engineer, BI Developer, Database Developer, Analytics Engineer, Data Analyst with strong technical skills, or Software Developer whose work has increasingly focused on data.

They do not need to arrive as an expert in Azure, Snowflake, Databricks, data architecture, or large-scale cloud engineering. More important is a strong foundation in SQL, logical problem solving, data manipulation, and basic programming, combined with enough professional experience to understand concepts such as source systems, production data, testing, version control, documentation, and downstream dependencies.

The successful candidate is curious about what happens to data before it reaches a dashboard or analytical model. When a number appears wrong, they want to understand where it came from, how it was transformed, and where the discrepancy entered the process. When a pipeline fails, they can investigate the problem methodically rather than simply rerunning the job.

This role is intended to provide a strong foundation for continued development within Data Engineering. With experience, the Data Engineer I should progress from developing defined pipeline components and resolving straightforward technical issues toward independently designing integrations, building more complex data solutions, optimizing performance, and contributing more substantially to enterprise data architecture.

Worksite and Sponsorship:

This is a full-time, direct-hire position what will work a minimum of two days per week from HNI's offices in downtown Chicago (near the Merchandise Mart. Candidates seeking fully remote work arrangements or who cannot commit to this level of onsite presence will not be considered. Employment based sponsorship IS NOT available for this position. Candidates requiring employment based sponsorship (now or in the future) to work at HNI will not be considered.

Essential Duties:

Data Pipeline Development

• Develop, test, deploy, and maintain data pipelines used to ingest, transform, and deliver enterprise data.
• Build ETL/ELT processes using SQL, Python, cloud-native technologies, and established data engineering frameworks.
• Extract data from enterprise applications, databases, files, APIs, and other approved data sources.
• Transform source data into standardized structures appropriate for analytics, reporting, and downstream applications.
• Develop pipeline components according to established architecture, naming conventions, coding standards, and engineering practices.
• Modify existing pipelines to support new data requirements, source-system changes, and business needs.
• Document pipeline logic, dependencies, data sources, transformations, and expected outputs.
• Participate in code reviews and incorporate feedback from more experienced engineers.

SQL & Data Transformation

• Write and maintain SQL used for data extraction, transformation, validation, and loading.
• Join and integrate information from multiple source systems according to defined business and technical requirements.
• Review query execution and identify straightforward opportunities to improve performance.
• Troubleshoot SQL errors, unexpected results, and data discrepancies.
• Apply established data modeling principles when creating or modifying tables, views, and related data structures.

• Work with Microsoft Azure data services and Snowflake to ingest, transform, store, and deliver data.
• Support data pipelines, data lakes, data warehouses, and related cloud-based data services.
• Follow established architecture and deployment patterns when creating cloud data solutions.
• Develop familiarity with technologies such as Azure Data Factory, Azure Data Lake, Azure Synapse, Databricks, Snowflake, or comparable cloud data platforms.

• Support integration of data from enterprise applications and other operational systems into HNI's analytics environment.
• Develop an understanding of source-system structures, data relationships, and business rules necessary to integrate information accurately.
• Assist with ingestion of structured and semi-structured data from databases, APIs, files, and other sources.
• Develop transformations that standardize information originating from different systems or business entities.
• Assist with troubleshooting integration failures and data synchronization issues.
• Maintain documentation describing important data sources, dependencies, and transformations.

• Build validation and quality checks into data pipelines and transformation processes.
• Test data outputs for completeness, accuracy, consistency, and expected business behavior.
• Investigate missing, duplicate, inconsistent, or unexpected data.
• Develop or maintain automated data-quality checks where appropriate.
• Follow established processes for resolving production data-quality issues.

• Support development and maintenance of enterprise data warehouse and data lake environments.
• Create and modify tables, views, transformations, and related data structures under established architectural standards.
• Assist with organizing data so that it can be efficiently accessed by reporting, analytics, and decision-science applications.
• Support testing associated with changes to shared data structures.

• Partner with Business Intelligence, Decision Science, Digital Experience, and other data consumers to understand technical data requirements.
• Develop datasets and data pipelines that support dashboards, reporting, analytics, and other business intelligence solutions.
• Help analysts understand the availability, structure, and appropriate use of enterprise data.

• Monitor assigned pipelines, workflows, and data processes for successful execution.
• Respond to alerts, failed jobs, data-quality issues, and other production problems.
• Troubleshoot straightforward failures involving SQL, transformations, pipeline configurations, source data, and dependencies.
• Participate in root-cause analysis for recurring data issues.
• Develop fixes that reduce repeated manual intervention.
• Document common issues and resolutions to strengthen team knowledge and operational support.

Experience & Qualifications

• Bachelor's degree inComputer Science, Data Engineering, Information Systems, Software Engineering, Data Analytics, or a related technical discipline preferred.
• Equivalent combinations of education, technical training, and relevant professional experience may be considered.
• 1-3 years of professional experience in data engineering, database development, software development, business intelligence, data analytics, or a related technical discipline.
• Professional, internship, co-op, or substantial project experience developing data solutions using SQL.
• Experience with Python or another programming or scripting language used for data processing.
• Exposure to ETL/ELT concepts and data-integration processes.

Preferred Qualifications

• Experience working with relational databases and basic data-modeling concepts.
• Exposure to cloud-based data platforms or services preferred.
• Experience with version control and structured software-development practices preferred.
• SQL: Working proficiency writing queries, joins, aggregations, transformations, and data-validation logic.
• Python: Foundational proficiency using Python for data manipulation, automation, or related development.
• ETL/ELT: Understanding of data extraction, transformation, loading, and pipeline concepts.
• Databases: Understanding of relational databases, tables, views, schemas, keys, and basic data-modeling principles.
• Data Quality: Understanding of techniques for validating completeness, accuracy, consistency, and reliability of data.

We look forward to hearing from you!

HNI Corporation(NYSE: HNI) is a manufacturer of workplace furnishings and building products, operating under two segments. Theworkplace furnishings segmentis a leading global designer and provider of commercial furnishings, going to market under multiple unique brands. Theresidential building products segmentis the nation's leading manufacturer and marketer of hearth products.

As one of the larger employers in Iowa, HNI Corporation was recognized in 2018, 2019, and 2020 for the diversity of our Board of Directors and was named in 2020, 2021, and #6 in 2022 as one of America's Most Responsible Companies by Newsweek.

How we act today protects how we live tomorrow. Check out our CSR Report here:https://www.hnicorp.com/social-responsibility

Diversity, equity, and inclusion (DEI), are not just core beliefs at HNI - they are operational imperatives. We value each other's differences in experiences and ideas to solve problems and better serve our customers.Take a look at our DEI goals here:https://www.hnicorp.com/diversity-equity-and-inclusion

We offer Benefits on Day 1, including a new voluntary benefit, Daily Pay! To learn about all the benefits HNI has to offer visit www.HNIbenefits.com.

We also invite you to visit us atwww.HNICorp.comto learn more!

HNI Corporation (NYSE: HNI) is a manufacturer of workplace furnishings and building products, operating under two segments. The workplace furnishings segment is a leading global designer and provider of commercial furnishings, going to market under multiple unique brands. The residential building products segment is the nation's leading manufacturer and marketer of hearth products.
We offer benefits starting from Day 1. To learn more, visit www.HNIbenefits.com.
Our company endeavors to make www.hnicareers.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at 563-272-7400 or via email at [emailprotected] Company is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, disability, protected veteran status, or other characteristics protected by law.