Grainger
Senior Staff Data Engineer
Grainger, Chicago, Illinois, United States, 60290
As a leading industrial distributor with operations primarily in North America, Japan, and the United Kingdom, we keep the world working by serving more than 4.5 million customers worldwide with products delivered through innovative technology and deep customer relationships. With 2023 sales of $16.5 billion, we're dedicated to providing value for customers, fostering an engaging culture for team members, and driving strong financial results.Our welcoming workplace enables you to learn, grow, and make a difference by keeping businesses running and their people safe. As a 2024 Glassdoor Best Place to Work and a Great Place to Work-Certified company, we're looking for passionate people to join our team as we continue leading the industry over our next 100 years.Position Details:
We are looking for a Senior Staff Data Engineer on our Customer Information Management (CIM) team. The team's primary mission is to build analytical data products by creating, gathering, maintaining, and operationalizing real-world information about our customers to drive growth actions across sales and marketing.You will be responsible for helping design and develop data pipelines and data products. You will work with SMEs, architects, analysts, data scientists, stakeholders, and others to build solutions that integrate, process, and store data from many of our internal and external enterprise data sources.This role will be reporting to the Manager, CIM, Product Engineering and is based out of Chicago.You Will:
Enable analytics and reporting by centralizing and integrating high quality, large, complex data sets in a highly performant and scalable cloud analytical platform.Work closely with architects, stakeholders, and product teams to implement data pipelines to ingest, cleanse, and enrich data for analytics to downstream stakeholders.Design and implement secure, performant data models to meet the scalability and performance needs of data product.Understand trends and emerging technologies and evaluate the performance and applicability of potential tools for our requirements.Build data models with DBT to transform data and ensure data quality by creating DBT unit tests.Build and maintain the data quality dashboards in Streamlit.Partner with stakeholders including data, design, product, and executive teams and assist them with data-related technical issues.Develop data products/systems using large and complex data sets to meet business and technical requirements.Work with product and business to define roadmap, communication, and architecture.Promote effective team practices, shape team culture, and engage in active mentoring.Pair program with developers daily to ensure better quality code, shared knowledge, and increased resiliency of our applications.Advocate for best practices on the team and prescribe coding and testing standards and tools.Work across the CIM Domain to establish best practices and coherent ways of working between and within teams.You Have:
10 years of experience with Modern Data Engineering projects and practices: designing, building, and deploying scalable data pipelines.5+ years of experience in designing, building, and deploying cloud-native solutions.At least 3 years of experience with AWS, Snowflake, DBT, Airflow/Astronomer, Python, Docker/Kubernetes, CI/CD, Git, familiarity with Databricks.Experience in working closely with architects to design and develop data lake, data pipelines, and data product publication strategy. Familiarity with: Data mesh architecture.Experience designing and implementing efficient, reusable, and scalable data processing systems and pipelines in Databricks and Snowflake.Educate and mentor the junior data engineers on data engineering best practices.Experience partnering with internal departments to establish requirements.Proven experience collaborating across teams to develop and implement data engineering best practices.Exposure to analytics and machine learning.Familiarity with BI tools such as Tableau, PowerBI.Rewards and Benefits:
With benefits starting day one, Grainger is committed to your safety, health, and wellbeing. Our programs provide choice and flexibility to meet our team members' individual needs. Check out some of the rewards available to you at Grainger.Medical, dental, vision, and life insurance plans.Generous paid time off (PTO) and 6 company holidays per year.Automatic 6% 401(k) company contribution each pay period.Employee discounts, parental leave, 3:1 match on donations, and tuition reimbursement.A comprehensive set of emotional, financial, physical, and social wellbeing programs.We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace.We are committed to fostering an inclusive, accessible environment that includes both providing reasonable accommodations to individuals with disabilities during the application and hiring process as well as throughout the course of one's employment. With this in mind, should you need a reasonable accommodation during the application and selection process, please advise us so that we can provide appropriate assistance.
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We are looking for a Senior Staff Data Engineer on our Customer Information Management (CIM) team. The team's primary mission is to build analytical data products by creating, gathering, maintaining, and operationalizing real-world information about our customers to drive growth actions across sales and marketing.You will be responsible for helping design and develop data pipelines and data products. You will work with SMEs, architects, analysts, data scientists, stakeholders, and others to build solutions that integrate, process, and store data from many of our internal and external enterprise data sources.This role will be reporting to the Manager, CIM, Product Engineering and is based out of Chicago.You Will:
Enable analytics and reporting by centralizing and integrating high quality, large, complex data sets in a highly performant and scalable cloud analytical platform.Work closely with architects, stakeholders, and product teams to implement data pipelines to ingest, cleanse, and enrich data for analytics to downstream stakeholders.Design and implement secure, performant data models to meet the scalability and performance needs of data product.Understand trends and emerging technologies and evaluate the performance and applicability of potential tools for our requirements.Build data models with DBT to transform data and ensure data quality by creating DBT unit tests.Build and maintain the data quality dashboards in Streamlit.Partner with stakeholders including data, design, product, and executive teams and assist them with data-related technical issues.Develop data products/systems using large and complex data sets to meet business and technical requirements.Work with product and business to define roadmap, communication, and architecture.Promote effective team practices, shape team culture, and engage in active mentoring.Pair program with developers daily to ensure better quality code, shared knowledge, and increased resiliency of our applications.Advocate for best practices on the team and prescribe coding and testing standards and tools.Work across the CIM Domain to establish best practices and coherent ways of working between and within teams.You Have:
10 years of experience with Modern Data Engineering projects and practices: designing, building, and deploying scalable data pipelines.5+ years of experience in designing, building, and deploying cloud-native solutions.At least 3 years of experience with AWS, Snowflake, DBT, Airflow/Astronomer, Python, Docker/Kubernetes, CI/CD, Git, familiarity with Databricks.Experience in working closely with architects to design and develop data lake, data pipelines, and data product publication strategy. Familiarity with: Data mesh architecture.Experience designing and implementing efficient, reusable, and scalable data processing systems and pipelines in Databricks and Snowflake.Educate and mentor the junior data engineers on data engineering best practices.Experience partnering with internal departments to establish requirements.Proven experience collaborating across teams to develop and implement data engineering best practices.Exposure to analytics and machine learning.Familiarity with BI tools such as Tableau, PowerBI.Rewards and Benefits:
With benefits starting day one, Grainger is committed to your safety, health, and wellbeing. Our programs provide choice and flexibility to meet our team members' individual needs. Check out some of the rewards available to you at Grainger.Medical, dental, vision, and life insurance plans.Generous paid time off (PTO) and 6 company holidays per year.Automatic 6% 401(k) company contribution each pay period.Employee discounts, parental leave, 3:1 match on donations, and tuition reimbursement.A comprehensive set of emotional, financial, physical, and social wellbeing programs.We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace.We are committed to fostering an inclusive, accessible environment that includes both providing reasonable accommodations to individuals with disabilities during the application and hiring process as well as throughout the course of one's employment. With this in mind, should you need a reasonable accommodation during the application and selection process, please advise us so that we can provide appropriate assistance.
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