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Manager, Data/ETL Engineering

Date: Jan 30, 2019

Location: LAKE FOREST, IL, US, 600455202

Company: Grainger

Data Engineering Manager

Company Overview


Grainger is a global leading broad line supplier of facilities maintenance products serving businesses and institutions. Our 18,000 employees are driven to serve customers and the community in exceptional ways focusing on delivering the highest level of service. The Grainger team works closely with customers to better understand their challenges and provide cost-saving solutions. Grainger's employees serve customers more than 115,000 times every day through multiple channels. As part of a high-performing team, you’ll be able to develop your talents, and make a difference. Grainger is a Fortune 500 company and a perennial member of Fortune magazine's Most Admired Companies list.

 

 Position Description

 

Grainger is seeking a Manager of Data Engineering for our Information Management practice.  The role will be focused on delivery and support for our current data warehouse/big data platforms as well as helping to deliver cloud-centric projects leveraging leading edge technologies.  The ideal candidate has prior experience leading data engineers, experience building on a cloud technology provider (AWS/Azure/GCP), and deep experience in traditional relational databases, data integration, and big data.  The Manager of Data Engineering will be involved in growing and expanding a highly-skilled group of onshore and offshore developers. 

This position can be based in either downtown Chicago or Lake Forest, Illinois with occasional travel between the two locations. 

 

Duties and Responsibilities

 

  • Manage a team of 15-25 Data Engineers split between onshore and offshore.
  • Own data engineering project delivery across numerous, disparate initiatives.
  • Support multiple data-rich environments including a Teradata and Hadoop installation leveraged by 2,500+ users.
  • Heavily participate in the development of a new, cloud-based modern data warehouse.
  • Develop data engineering best practices, guidelines, procedures, and repeatable/scalable frameworks.
  • Document, automate, and enforce data quality, data integrity, and QA best practices.
  • Continuously improve data environments to ensure they are highly performant and provide an optimal end user experience.
  • Partner extensively with the business user community to ensure that your team(s) are meeting their needs and consistently delivering value.
  • Provide mentorship, guidance, and career development for your direct reports.

Position Requirements

 

  • 8+ years of experience in Data Warehousing and Analytics with demonstrable experience in data integration and data warehouse projects.
  • 3+ years of experience with big data technologies (Hadoop, Sqoop, Hue, MapReduce, Kafka, Hive, Spark)
  • 2+ years of experience building on Cloud technology providers (preference for AWS but open to Azure or GCP) 
  • 2+ years of working in an onshore/offshore model
  • Extensive experience successfully delivering numerous data warehousing projects including data warehouse transformational initiatives.
  • Prior experience with Teradata or SAP BW a plus.
  • Hands on experience hiring or building teams of data engineers.
  • Experience with automation via ETL tools (i.e. Informatica, WhereScape, SSIS, etc…)
  • Experience working with code repositories and continuous integration (i.e. Git, Jenkins, etc..)
  • Coding proficiency in at least one modern programming language (i.e. Python, Scala, or Java)    
  • Experience leading a team in an agile development environment.
  • Possess a high emotional IQ.  Be attuned to the needs of your team.
  • Attention to detail, excellent problem-solving ability, and strong communication skills (written and verbal).
  • A bachelor’s degree in Computer Science, related field, or equivalent experience

 

Grainger is an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or protected ve


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