Data Analyst (Agile/SQL)

Location: Philadelphia PA Hybrid Model - Unable to consider 100% remote requests

Data Analyst:

The team’s focus is uniform access and complete transparency for data assets to enable informed business decisions that drive profitable growth. Manage the complete project lifecycle for new data integration, data integrity and data standardization centered on single source of truth.

Required Skills and Experience:

• Bachelor’s degree in Computer Science, Information Technology or related field desired
• Following knowledge and experience as noted
  • SQL – required
  • Requirement Gathering - required
  • AWS / Hadoop / Horton Works – plus
  • Small & Medium Business (SMB) Data Mart Experience - plus
  • Teradata – plus
  • Informatica - plus
• Minimum of 5 years relevant work experience
• Ability to analyze data and work independently
• Good organizational and interpersonal skills with the ability to work with various functional areas, including field, Region, Division and Corporate personnel

Responsibilities:

• Collaborate across multiple teams to understand business needs, analyze complex data, and integrate Business data with other Enterprise data assets
• Become the subject matter expert in the data and be able to articulate how it benefits business stakeholders
• Work with business units to document the requirements for enterprise base & semantic layer
• Identify and build source to target mapping for Business data attributes.
• Work with management team in estimating level of effort and timelines
• Need to maintain detailed documentation through data lifecycle processing to ensure fully transparent communication and meeting deadline expectations
• Develop the business rules and logic in order to harmonize the data
• Own creation of test plans and execution of User Acceptance Testing for stated data dependent projects
• Partner with HQ systems engineering and business units to process data in stage, journal, base and semantic within Teradata and AWS / Hadoop / Horton Works
• Partner with data architecture and project management teams throughout the project lifecycle
• Support standardization efforts for referential data used for data analysis and project output
• Provide regular status updates to leadership team