Senior Data Analyst

Responsibilities:

•  Increase data availability, standardization, and automation processes.
•  Problem solve and investigate issues.
•  Participate in all phases of system testing.
•  Work successfully in an Agile Project across multiple feature and component teams.
• Complete estimates and work plans in Program Increments (PI) Meetings as appropriate for design, development, implementation, and rollout tasks.
• Articulate and/or translate business problem statements to data requirements to proactively work on design and analysis prior to system design for timely delivery.
•  Understand and review existing data models and patterns to identify improvements, recommend improvements in functionality, performance, etc.
•  Ideate and develop multiple options for any given problem and present with sound logic and reasoning.
• Learn and work in a fast-changing technology landscape to design retail systems of the future.
•  Become familiar with store and supply chain systems and sources of truth for various master data.
•  Recommend and present analysis on data as required.
• Coordinate and align all other technology teams to ensure operational delivery processes are governed and monitored to expedite issue remediation

REQUIREMENTS:

•  Demonstrates solid understanding of architectural components and system design principles for effective contribution to all design discussions.
•  Well-versed with the concepts and application of entity definition, idempotency, normalization/de-normalization of relational models, naming convention, data types, dimensional modeling, and modeling for key-value based databases.
•  Optional: Proficient in using and designing with Erwin Data Modeler for SQL Server, Cassandra, Kafka, MS Azure Databases and Data Stores, or other similar technologies.
• The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. 

Key Skills:

• Statistics and mathematics.
• Data management and infrastructure.
• Critical thinking.
• Verbal and written communication.
• Problem solving.
• Programming and coding.
• Data interpretation and presentation.