Business Intelligence Analyst, Operations

NextLink•Hudson Oaks, TX

2d•Onsite

About The Position

The Business Intelligence Analyst transforms raw operational and customer data into clear, decision-ready reporting and dashboards for leaders across the organization. This role sits at the intersection of reporting and data quality: you will not only build the metrics the business runs on, but also actively investigate company records to find, diagnose, and resolve data issues before they reach a report. You will partner with operations, finance, network, and customer-experience teams to make sure the numbers everyone relies on are accurate, consistent, and trustworthy.

Requirements

Bachelor’s degree in a quantitative, business, information systems, or related field — or equivalent practical experience.
2–5 years of experience in business intelligence, data analysis, reporting, or a closely related role.
Proficiency in SQL for querying, joining, and validating data across large datasets.
Hands-on experience building dashboards and reports in Tableau.
Strong skills in Excel and/or Power BI for analysis, modeling, and reporting.
Working knowledge of Python for data cleanup, automation, and analysis.
Comfort using AI tools to improve speed and quality of analysis and documentation.
Demonstrated attention to detail and a track record of finding and fixing data-quality issues.
Ability to communicate technical findings clearly to non-technical audiences.

Nice To Haves

Experience in telecommunications, ISP, utilities, or another operations-heavy industry.
Familiarity with data-warehouse concepts, ETL/data pipelines, and data governance practices.
Experience reconciling data across multiple business systems (billing, CRM, ticketing, network monitoring).
Exposure to statistical analysis or forecasting techniques.

Responsibilities

Design, build, and maintain dashboards and recurring reports that track KPIs across operations, customer churn, network performance, labor, and finance.
Translate business questions from stakeholders into well-defined metrics, data models, and visualizations.
Automate manual and repetitive reporting so teams get timely, self-service access to the data they need.
Present findings and trends in clear, executive-ready formats and explain the “so what” behind the numbers.
Proactively audit company records and source systems to identify inaccuracies, duplicates, gaps, and inconsistencies.
Investigate root causes of data discrepancies and reconcile mismatches across systems (e.g., billing, ticketing, network, and HR data).
Correct data issues at the source where possible and document fixes; partner with system and data owners to prevent recurrence.
Establish and monitor data-quality checks, validation rules, and alerts to catch problems early.
Perform ad-hoc analysis to support operational and strategic decisions.
Document data definitions, sources, and reporting logic so metrics are consistent and reproducible across teams.
Collaborate with cross-functional stakeholders to understand workflows and ensure reporting reflects how the business actually operates.
Use AI tools to accelerate analysis, automate data-cleanup workflows, draft documentation, and surface anomalies faster.