Senior Data Engineer

Graco manufactures and markets premium equipment to move, measure, control, dispense and spray a wide variety of fluid and powder materials. What does that mean? Well, we pump peanut butter into your jar, and the oil in your car. We glue the soles of your shoes, the glass in your windows and the screen on your phone. We spray the finish on your vehicle, coatings on your pills, the paint on your house and texture on your walls. Graco is part of your daily life.

The Senior Data Engineer will engineer and manage robust data pipelines that ensure seamless, secure, and efficient data integration and transformation across the enterprise. Reporting to the Manager of Data Platforms, the Senior Data Engineer will collaborate with operational and business partners, help to execute solutions that align with our data strategy, and propel organizational objectives.

What You Will Do at Graco

Data Management Strategy 

• Designs, develops, and maintains scalable and efficient data pipelines for collecting, processing, consuming, and storing datasets. 

• Implement data management practices to ensure data quality, including data cleansing, normalization, and validation techniques. 

• Develop and maintain data warehouses, data lakes, ensuring efficient storage and retrieval of data assets. 

• Implement data security measures, to protect sensitive information and ensure compliance with industry standards and regulations. 

• Monitor and audit data access and usage to detect and prevent unauthorized access. 

• Integrates data from various sources, including databases, data warehouses, APIs, and external systems. 

• Ensures data consistency and integrity during the integration process, performing data validation and cleaning as needed. 

• Ensure the reliability and scalability of near real-time data pipelines. 

• Optimize data pipelines and data processing workflows for performance, scalability, and efficiency. 

• Monitors and tunes data systems, identifies and resolves performance bottlenecks, and implements caching and indexing strategies to enhance query performance. 

• Takes authority, responsibility, and accountability for exploiting the value of enterprise information assets and of the analytics used to render insights for decision making automated decisions and augmentation of human performance. 

• Works with Director of Data and Analytics and Data Platform Manager to establish the vision for managing data as a business capability. 

Advanced Analytics & Insights 

• Transforms raw data into a usable format by applying data cleansing, aggregation, filtering, and enrichment techniques. 

• Leverage advanced analytics to drive business insights.  

• Collaborate closely with data analysts to ensure data accuracy and integrity, and help in translating complex data into clear, actionable insights. 

Compliance and Risk Management 

• Establishes the governance of data and algorithms used for analysis, analytical applications, and automated decision making. 

• Implements data quality checks and validations within data pipelines to ensure the accuracy, consistency, and completeness of data. 

Cross-Functional Collaboration and Stakeholder Engagement 

• Ability to collaborate within and across teams of different technical knowledge to support delivery and educate end users on data products. 

• Collaborates with business analysts to optimize models and algorithms for data quality, security, and governance. 

• Partner with various departments and business groups across the organization to understand their data needs and translate them into data solutions.  

• Liaise with stakeholders across the organization, including executives, product managers, software developers, data analysts, data scientists, to define data requirements, and ensure data strategies and solutions align with organizational objectives. 

What You Will Bring to Graco

• Bachelor’s degree in computer science, data science, software engineering, information systems, or related quantitative field

• 5+ years of work experience in data management disciplines, including data integration, modeling, governance, security, optimization and quality, or other areas directly relevant to data engineering responsibilities and tasks 

• Expert knowledge in technologies such as Fivetran, Kafka, Airflow, and Spark to build scalable and efficient data pipelines. 

• Ability to design, build, and deploy data solutions that capture, explore, transform, and utilize data to support AI, ML, and BI.