Senior Data Modeler
- 225 S Sepulveda Blvd, Manhattan Beach, CA 90266, USA
- Employment Status: Regular
Join the thousands of innovators, advocates and forces who are making an impact every day at one of the biggest footwear brands in the world. Whether you love to connect with consumers on the retail floor or want to drive our award-winning powerhouse in new directions, the SKECHERS team is the place to be. Learn more about our brand at skx.com.
As a member of the Information Technology (IT) team, the Data Modeler is critical in providing leadership with ongoing analysis, design, and implementation of changes to the multidimensional data model any future Decision support systems that will form the backbone of the Big Data ecosystem. You will join a tight-knit group of key contributors within the Data Engineering team who are actively working together to achieve aggressive goals and meet timelines to drive the business forward.
Essential Job Results
Identify Business Needs:
- Assess/capture/translate into structured analytics use-case, including rapid learning of industry-domain
- Define business systems’ data-consumption requirements
- Business activities improvement opportunities with data
- Understand data flows and propose/implement data solutions
Create and Maintain Data Models:
- Utilize structured approaches to solving problems and documenting risks & assumptions
- Work closely with business and data analysts to create data-models at multiple levels (e.g., capture, semantic)
- Create and maintain data maps and diagrams for data domains and systems
- These data models may encompass working with Big Data technologies (e.g. Hive, Hbase, Casandra), data warehousing, data science, metadata repositories master data management including the use of standardized vocabularies, code sets & ontologies, where appropriate.
Contribute to Skechers Data Standards:
- Data Modeling and Design Standards
- Tools, best practices and related development methodologies
- Data security, lifecycle and retention architecture
- Ensure adherence to technical database design standards in accordance with the approved enterprise data modeling and database design standards
- Toward standardization and proper data usage, based on analyses
- Communicate the benefits and ROI for Skechers Data Engineering, extending to enterprise platform owners
The ideal candidate is an analytical and creative thinker who is not intimidated by roadblocks and challenges. Successful evaluation of problems and development of appropriate solutions, adhering to internal guidelines and regulatory compliance needs should be part of daily tasks. A successful Data Modeler can be counted on to perform reasonably well under pressure, focusing while completing assigned-scope projects efficiently.
- Strong aptitude for quickly learning business operational, process, delivery models
- Create and graphically represent data, for analysis and design purposes towards Data Warehouse and Data Mart implementation patterns, such as Kimball and Inmon methodologies.
- Ability to work in a dynamic and agile environment with changing requirements and priorities often requiring virtual and face-to-face interactions
- Proven Experience in Dimensional Modeling (Star Schema, OLAP Cubes, and Bus Matrix Mapping)
- Translating/mapping relational data models to conceptual, logical and physical schema additionally experience translating business requirements into Data Structure requirements and logical and physical model
- Advanced technical knowledge and background in the areas of Data modeling, EDW, Data Mart, data management, Data Quality, Data Governance, Data Security, Data integration (ETL) and Data Migration
- Ability to take direction to define and implement solutions as requirements are being identified and finalized whilst keeping the big picture in mind to ensure that the pieces make up the final solution
- At least one Data Management implementation on AWS or Azure
- Thorough understanding of modern data platform components and options on Cloud market place and specifically experience with modern data architectures
- Review DB design with development teams, and generate initial Data Definition Language (DDL), as needed.
- In depth understanding in system development life cycle and successfully deployed reliable data systems and data quality management systems
- Ability to work effectively with both business and technical stakeholders as well as ability to work independently to conduct self-directed research
- Strong written and verbal communication skills to influence others
Experience and Education
- 7+ years of experience defining, designing and delivering data warehousing solutions
- At least 3 years’ experience in the development of data models using Data Modeling tools.
- Minimum of 3 years of work experience:
- Extracting, preparing, munging, validating data
- Building data-models for analytics pipelines and/or data-science landscape
- Strong knowledge in design and building of data and metadata extractions,
- Work with the non-technical business units to understand available resources and constraints around data (sources, integrity and definitions)
- Working on Big Data modeling, data warehousing, SQL and metadata management
- Familiar with modern analytics tools and programming languages, such as SQL, Python, Apache Spark, Alteryx, etc.
- 1+ year experience with cloud-based data warehousing systems (e.g. AWS Redshift, Snowflake, Google Big Query)
- Experience with Business Intelligence (BI) tools for insight-presentation experience (e.g., Tableau, PowerBI, etc)
· Bachelor’s degree from an accredited college/university in an applied quantitative discipline, such as Data Science, Analytics, Computer Science, Engineering or equivalent experience
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The skills, abilities and physical demands described are representative of those duties that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities, who are otherwise qualified for the job position, to perform the essential functions.
While performing the duties of this job, the employee is regularly required to stand; use hands to finger, handle, or feel, and talk or hear. The employee frequently is required to walk; sit, reach with hands and arms, and stoop, kneel. The employee is occasionally required to sit for long period of times.