Boise Hybrid Data Analyst: Analytics & AI Solutions

Ericsson GmbH

Boise (ID)

Hybrid

USD 65,000 - 90,000

Full time

14 days+

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Benefits offered by this job

401(k) plan with 4% match

Health insurance

Paid time off

Job summary

Ericsson Enterprise Wireless Solutions is seeking a Data Analyst based in Boise, ID, for a hybrid role with three onsite days per week. You will support requirements gathering, EDA, and specifications for analytics, data, and AI-enabled solutions, bridging business and technical teams.

Responsibilities include documenting requirements, user stories, and acceptance criteria; performing SQL-based data validation; collaborating with data engineers and BI developers; and coordinating delivery with

Qualifications

Bachelor's degree in Business Analytics, Information Systems, Data Analytics, Computer Science, Finance, or equivalent practical experience.
2+ years of experience in a data analyst, business analyst, BI analyst, product analyst, or similar requirements-focused role.
1–2 years of hands-on SQL experience (joins, filters, aggregations, CTEs, exploratory profiling).
Demonstrated ability to gather stakeholder requirements and translate them into clear documentation for technical teams.
Strong written and verbal communication skills; able to adapt style for both technical and non-technical audiences.
Experience with data visualization tools such as Tableau, Power BI, or equivalent.
Understanding of data warehousing concepts (tables, views, dimensions, facts, grain).
Strong organizational skills with the ability to manage multiple workstreams and follow through on commitments.

Responsibilities

Partner with business stakeholders to gather, clarify, and document requirements for analytics, reporting, data products, semantic models, and AI-enabled solutions.
Translate ambiguous business requests into structured problem statements, user stories, acceptance criteria, and technical specifications.
Conduct exploratory data analysis using SQL to validate assumptions, assess data availability, and identify data quality issues.
Collaborate with data engineers, analytics engineers, BI developers, and AI/ML practitioners to ensure business logic is accurately reflected in delivered solutions.
Facilitate discovery sessions, requirements workshops, stakeholder interviews, and cross-functional alignment meetings.
Create and maintain documentation including business requirements documents, process flows, metric definitions, test scenarios, and decision logs.
Support Agile delivery by writing user stories, documenting acceptance criteria, and participating in sprint planning and prioritization.
Identify gaps between stakeholder expectations, available data, and technical feasibility; proactively communicate risks and tradeoffs.
Support user acceptance testing and promote consistent use of data definitions and standardized analytics practices.