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Major League Soccer is seeking a Data Architect to help us define and build our data strategy and our data engineering team.
This person will live within our engineering department but partner with all departments in Major League Soccer to extend and refine our growing data and analytics needs by evaluating all aspects of our enterprise data.
This position will be involved in all aspects of our data strategy from inception to execution and is responsible for helping strategize, proof of concept and present how we will use data to drive business decisions and initiatives moving forward.
Our departments new mandate is to reimagine how our league uses data to drive its decisions. If this sounds exciting, then we would love to talk to you.
Help create and be a major influencer in the vision for the Major League Soccer Centralized Data Strategy
Create a POC to validate centralization data lake plan
Partner with cross functional teams to build shared goals
Build relationships across the entire organization with all major stakeholders
Manage data warehouse plans and roadmap across the organization
Ensure high levels of data quality across the product vertical and related business areas
Manage the delivery of data dashboards and visualizations
Develop Data Quality checks for source and target data sets. Develop UAT plans and conduct QA.
Develop and maintain ETL routines using ETL and orchestration tools
Eventually Build a high-quality BI and Data Warehousing team
Manage development of data team resources to support business initiatives
Present and advocate for UX work with teams across the organization
Lead user research efforts to inform UX and design decisions
Ensure that the final product maintains a high standard through attention to detail and collaboration with engineering at every step
Maintain and extend our existing Experience Design style and component libraries
Manage experience design tooling and processes
Bachelor’s Degree in an analytical field such as economics, mathematics, or computer science is desired.
6+ years of relevant professional experience with 3+ years in direct people management capacity
Experience scaling and managing a small team
Experience in building data warehousing environments. Strong background of data modeling principles including Dimensional modeling, data normalization principles etc.
Experience with BigData technologies and working with traditional relational databases and big data distributed systems such as Spark, Hadoop / Hive, BigQuery, Redshift, etc.
Experience programming languages (ie Python, Ruby, Java).
Experience with workflow processing tools (ie. Step Functions, Azkaban, etc)
Strong Project and Program Management experience.
Proven experience communicating and collaborating with stakeholders across multiple functions