Job Title
Analytics EngineerPosition Overview
Shaw Industries Group, Inc. is a leader in flooring and other surface solutions designed for residential housing, commercial spaces and outdoor environments. Leveraging strengths in design, innovation and operational excellence, the company takes a people-centered, customer-focused, and growth-minded approach to meet diverse market needs. It creates differentiated customer experiences through its expansive portfolio of brands: Anderson Tuftex, COREtec, Shaw Floors, Patcraft, Philadelphia Commercial, Shaw Contract, Shaw Sports Turf, Shawgrass, Southwest Greens, Watershed Geo and more.
Headquartered in Dalton, Georgia, Shaw is a wholly owned subsidiary of Berkshire Hathaway, Inc. with more than $6 billion in annual sales and 18,000 associates worldwide.
Analytics Engineers are multidisciplined individuals whose skills sit at an intersection of Business Teams, Data Analytics, and Data Engineering, and are responsible for bringing robust, efficient, and integrated data models and analytic solutions to life. Analytics Engineers possess a high level of business acumen, as well as technical mastery, can speak in business terms, and are able to translate data insights and analysis needs into analytic models. Analytics Engineers thrive at being able to blend business acumen with technical expertise and transition between business strategy and data development. Analytics Engineers partner closely in a highly collaborative environment working with divisional & departmental leaders across Shaw’s Integrated Supply Chain (ISC) & Manufacturing Operations Division as well as Shaw’s Data Management Team to provide data driven analytical solutions which leads to business value, decision enablement, and behavior-based outcomes.
As members of the Analytics Center of Excellence for Global Operations, Analytics Engineers will be responsible for coaching & mentoring within Shaw’s business units to further enable self-service analytics across Shaw and provide governance over best practices for data visualization & analytic related activities. (Internal job profile is Data Analytics Engineer III)
This is a hybrid role that will work up to 3 days per week from Corporate offices Dalton, GA.
Responsibilities:
Analytics Engineers are responsible for helping to bridge the gap between business and technology thus requiring equal amounts of business and technical acumen.
Collaborate, consult, & advise with front-line managers and directors to collect business requirements, define successful analytic outcomes, and design supporting data models.
Possess business acumen in 2 or more of the following business areas: Corporate Planning, Global Sourcing, Manufacturing Operations, Customer Service, Logistics, Financial Services, Risk Management, Invoicing, Category Management, Manufacturing Operations, or Samples.
In this Intermediate role, 65% of your time will be spent as a developer working with an analytics team executing analytic solutions via the analytics development lifecycle. This time will be split across data discovery & design, analytic modeling, advanced analytics, and data visualization activities.
45% of this role’s time will be spent building and maintaining positive business relationships, advancing knowledge of technical tools & business acumen, coaching & developing business area analysts, and continuously learning to drive innovation.
Ability to lead at least 1 analytic project with a duration of 6+ months which may also span multiple business areas within the Supply Chain and / or Manufacturing Operations.
Partner closely with Business Leads to consult on Advanced Analytic capabilities and provide innovative approaches towards analytic solutions.
Develop and implement data & analytical development best practices to ensure confidence and trust in analytical solutions.
Assists the Analytics Center of Excellence to coach, influence, and provide DataOps & analytic governance to drive best practices and development standards across the enterprise.
Displays a genuine interest to develop business acumen and understanding of key business drivers that are used in the development of analytic solutions.
Design, develop, optimize, and maintain data architectures using advanced SQL capabilities inside of our Enterprise Data Layer - Databricks.
Conducts data cleansing exercises to ensure quality of data and analytic results.
Organize and transform data in a meaningful way to provide analytics ready result sets.
Create reusable data assets to be used by Business Insights Analysts, Data Scientists, and other Analytics Engineers.
Design, develop, optimize, and maintain end user data visualizations & analytic solutions using tools such as Tableau, PowerBI, Qlikview, R, RShiny, Splunk, Python, and other related tools to enable data mining & analytic capabilities.
Maintain the Data Catalog, Data Lineage, and Data Assets that supports Enterprise Data Management.
Solve complex data problems to deliver insights which are used to achieve business outcomes.
Works closely with Data Engineering to build and maintain complex databases as well as streamline processes to ensure that data is cleaner earlier in the data integration flow process.
Maintains supporting artifacts such as data models, architecture, and systems design diagrams to well describe the analytic solution.
Continually learn about Data Visualization, Machine Learning, Data Science, AI, Statistics, and other Advanced Analytics concepts.
Requirements:
Bachelor’s degree in Business, Business Analytics, Mathematics, Statistics, Computer Science, or a related field.
Minimum of 2 years of experience providing data engineering, data visualizations, and/or implementing descriptive, predictive, and prescriptive analytics solutions
Strong understanding of Tableau, SQL, R, Python, Azure, AWS
Travel may be required for facility support and conference attendance.
Preferred Technical Skills:
Strong SQL / ETL / Database Knowledge
Data Visualization tools such as Tableau, Qlikview, PowerBI, Splunk
Experience with Data Science tools such as R or Python.
Experience with Data Lakes such as Azure, AWS, or Hadoop
Experience with Databricks or similar product
Knowledge, Skills, and Abilities:
Ability to navigate ambiguity and quickly gain and apply understanding of business concepts to analytical solutions.
Understands overall Enterprise Data Architecture and demonstrates the ability to model complex data structures logically and physically to support analytical requirements.
Proven track record of independent thinking and innovative approaches to problem solving.
Excellent written, oral, and presentation skills.
Demonstrated ability to manage concurrent initiatives.
Understands the full lifecycle of analytic projects and DataOps concepts.
Ability to present ideas in a meaningful, business minded way, to diverse audiences.
Strong analytical and problem-solving abilities to uncover root causes
Strong customer service orientation.
Experience working in a team oriented, collaborative environment.
Ability to communicate technical information effectively to business users.
Competencies:
Execute Action Plan
Deliver Compelling Communication
Build Customer Satisfaction
Learn Continuously
Build Trusting Relationships
Facilitate Change
Position may be offered as a salary grade 6 or 7 based on years of experience and expertise within the capabilities described above.
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