Sr. Manager, Data Engineering

About the position

HNI Corporation is a global family of brands for the workplace and home dedicated to enhancing the spaces where we live, work, and gather. We pride ourselves on fostering an environment where we make a positive impact on others; upholding our beliefs in integrity, inclusion and belonging. We're hiring a Sr. Manager, Data Engineering to lead our data engineering team in designing, building, and optimizing scalable data solutions. This role will focus on leveraging Microsoft Azure and Snowflake to drive data architecture, ETL/ELT pipelines, and data governance best practices. The ideal candidate has a strong background in cloud data platforms, experience managing engineering teams, and a passion for delivering high-quality, data-driven solutions. This role will be responsible for end-to-end architecture, development, and optimization of enterprise data solutions that support critical business decision-making. The ideal candidate has extensive experience with Data Lakes, Python, CI/CD frameworks, SQL, and ETL/ELT development. This role requires both technical expertise and leadership skills to drive data innovation, enhance analytics capabilities, and ensure a scalable, high-performance data ecosystem.

Responsibilities

• Define the strategy for enterprise business intelligence tools, processes, and capabilities.
• Work closely with Analytics, Decision Science and Business teams to gather feedback on existing tools and help pilot new tools and capabilities.
• Lead the design and implementation of cloud-based data architectures and data models used for self-service analytics through Power BI.
• Oversee the design, development, and maintenance of data pipelines, warehouses, and other data infrastructure, ensuring data accuracy, reliability, and security.
• Collaborate with cross-functional teams to understand business needs and translate them into data engineering solutions.
• Craft a bold, exciting vision for BI and drive transformative innovation to enable next-gen data capabilities, especially through AI and self-serve analytics.
• Identify and implement innovative approaches to streamline data processes and improve data quality and efficiency.
• Provide technical leadership responsibilities and improve engagement in leading and inspiring teams in their performance and responsibilities.
• Effectively translate data complexity into clear, actionable insights for leaders while advocating for the team's impact to the business.
• Lead and mentor a team of data engineers, fostering a culture of innovation, continuous learning, and operational excellence.
• Define and implement best practices for data engineering, architecture, and operations.
• Stay ahead of industry trends and emerging technologies to drive innovation and enhance the organization's data capabilities.
• Create a collaborative, performance-driven work environment by facilitating and fostering trust, transparency, and inclusion.
• Work with team members to set clear goals, provide feedback, perform performance assessments, and support ongoing development.

Requirements

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 10+ years of experience in data architecture, data engineering, or business intelligence, with a focus on cloud platforms (Azure preferred).
• Expertise in SQL, developing ETL/ELT pipelines, and managing large-scale data processing.
• Expertise experience with Azure Data Lake, Spark, Airflow, Databricks, and other data services.
• Strong proficiency in Python for data transformation, automation, and analytics.
• Experience with CI/CD frameworks and version control tools for automated deployment and testing of data solutions.
• In-depth knowledge of relational databases and cloud.
• Strong understanding of data modeling, governance, and security best practices in cloud environments.
• Strong analytical, problem-solving, and communication skills, with the ability to translate business needs into technical solutions.
• Experience leading and mentoring a team of data professionals.