Business Analyst

TrueBlue Inc.; Newark (NJ); On-site; USD 70,000 - 110,000; Full time

Job summary

TrueBlue Inc. invites a Business Analyst to support data and analytics for a market data project, bridging business stakeholders and data engineering teams.

You will gather and shape requirements, assess data, validate accuracy and help deliver reliable data solutions that guide decision-making. This role suits someone with 2-5 years of experience who understands how data informs business decisions, learns new technologies quickly, and collaborates with offshore teams using Excel, SQL, Jira and

Qualifications

• 2-5 years in business analysis or data analytics.
• Understands how data can answer business questions.
• Profiles data in Excel and SQL; understands schemas, table structures and how data sets relate.
• Uses AI tools in day-to-day analysis and solutioning.
• Clear written and verbal communication; able to simplify technical ideas for business stakeholders.
• Curious and eager to learn new AI and data technologies.

Responsibilities

• Lead discovery sessions; write user stories, acceptance criteria and functional specs.
• Profile data sources in Excel and SQL; verify schemas and data gaps.
• Translate business needs to technical requirements; liaise with offshore teams.
• Use AI tools to analyze data and draft documentation.
• Write and execute UAT test cases to verify data accuracy and dashboard functionality.
• Maintain Jira backlog; participate in Agile ceremonies.
• Document in Confluence and enforce data quality guidelines.

Skills

Business analysis

Data analytics

SQL

Excel

Stakeholder communication

Agile / Scrum

Documentation

Tools

Jira

Confluence

Job description

The Business Analyst will support our data and analytics work for a market data project, acting as the bridge between business stakeholders and data engineering teams, including offshore teams. You will gather and shape business requirements, assess and profile data, validate data accuracy, and help deliver reliable data solutions that guide decision-making.

This role suits someone with 2-5 years of experience who understands how data is used in the business, learns new technology quickly, and wants to grow into an Engagement Manager role.

Key Responsibilities:

• Requirements Gathering: Lead discovery sessions with business stakeholders to document business needs; write clear user stories, acceptance criteria and functional specifications.
• Data Assessment: Profile and assess data sources using Excel and SQL; understand schemas and table structures; identify data gaps and confirm feasibility before data engineering work begins.
• Business and Tech Liaison: Work with business users and technology teams, including offshore teams, translating business needs into technical requirements and explaining technical constraints back to the business.
• AI-assisted Solutioning: Use AI tools to analyze data, draft documentation and explore solution options.
• Data Validation & UAT: Write and execute test cases during User Acceptance Testing (UAT), verifying data accuracy, integrity and dashboard functionality.
• Sprint Support: Maintain the backlog in Jira, participate in Agile ceremonies (daily stand-ups, sprint planning) and track task status.
• Documentation & Governance: Maintain clear documentation in Confluence and help enforce data standard operating procedures and data quality guidelines.

Qualifications:

• Experience: 2-5 years in business analysis, data analytics or a related role.
• Business Understanding: Understands business requirements and grasps quickly how data can be used to answer business questions.
• Data Concepts: Able to conceptualize and understand data, including market data, and how it flows between systems.
• Data Skills: Profiles data in Excel and SQL; understands schemas, table structures and how data sets relate.
• AI Tools: Uses AI tools in day-to-day analysis and solutioning.
• Communication: Clear written and verbal communication; able to simplify technical ideas for business stakeholders.
• Curiosity: Eager to learn new things, especially the latest developments in AI and data technology.

Good to Have (Not Required):

• Market data experience, for example Bloomberg, Reuters/LSEG or Morningstar.
• Experience working with offshore teams.
• Exposure to cloud data platforms (for example, Snowflake, Databricks or Azure) and ETL/ELT concepts.