Mid-Level Data Analyst

pureIntegration•Reston, VA

1d•$40 - $50•Remote

About The Position

We are seeking a Mid-Level Data Analyst to support data-driven decision-making across network reliability and subscriber experience initiatives. This role is responsible for performing structured analysis on large, complex datasets; identifying trends and contributing factors; and delivering clear, actionable insights to technical and operational stakeholders. This position is ideal for an analyst who can work independently on well-defined problems while also partnering closely with a senior lead on more complex investigations. The role emphasizes strong fundamentals in SQL, Excel, data visualization, and analytical reasoning, with a focus on answering both what happened and why it happened. The ideal candidate will be comfortable working with large-scale datasets, building repeatable analyses, and using data to support troubleshooting, operational improvement, and measurement of network changes. This position is fully remote within the U.S. and will be a W-2 hourly engagement for 6 to 9 months. The hourly range is $40/hr - $50/hr. Candidates will be paid based on their work experience and skills. Candidates are also eligible for limited benefits such as health insurance, professional development, training, our referral bonus program, and our wellness program.

Requirements

3–5 years of experience in data analysis, business intelligence, advanced reporting, or a related field.
Bachelor’s degree in Engineering, Computer Science, Statistics, Mathematics, Information Systems, or a related discipline, or equivalent professional experience.
Strong experience working with large datasets and performing structured analysis to identify trends, correlations, inconsistencies, and contributing factors.
Strong proficiency in Excel, including pivot tables, formulas, data manipulation, and reconciliation techniques.
Proficiency in SQL, including joins, aggregations, filtering, and the ability to write and refine queries independently.
Strong working proficiency in Tableau and MicroStrategy.
Python exposure required at a minimum for the ability to read and debug existing code; ability to write scripts is preferred.
Strong understanding of analytical fundamentals, including proper use of averages, weighted averages, rates, ratios, and other aggregation methods.
Demonstrated ability to translate data into clear findings and business-relevant insights.
Strong analytical, problem-solving, organizational, and communication skills.
Ability to manage multiple priorities and work effectively with both technical and business stakeholders.

Nice To Haves

Experience working with telecom, cable, broadband, video, DOCSIS, or network operations data.
Experience with AWS and Amazon Redshift environments.
Exposure to statistical analysis, causal inference, or experimental/non-experimental analytical methods.
Familiarity with additional business intelligence or visualization tools such as Power BI or Looker.

Responsibilities

Perform structured analysis on large-scale datasets to identify trends, patterns, anomalies, and potential drivers of service performance outcomes.
Write and execute SQL queries in Amazon Redshift to extract, join, and analyze data from established sources.
Use Excel as a primary analytical tool, including pivot tables, formulas, reconciliations, and purpose-built aggregations.
Develop, modify, and interpret dashboards and visualizations in Tableau and MicroStrategy to support exploratory and explanatory analysis.
Support hypothesis-driven investigations by segmenting data across dimensions such as geography, equipment, network configuration, and operational history.
Assist with before-and-after analyses and comparative studies to help determine whether changes improved or degraded outcomes.
Read and debug Python code used in analytical workflows, data validation, or lightweight automation; ability to write scripts is preferred but not required.
Apply an AI-aware analytical mindset by identifying opportunities to use AI tools to accelerate analysis, improve first-pass exploration, or strengthen communication of findings.
Prepare clear, well-structured summaries of findings for technical and non-technical stakeholders through email, PowerPoint, and supporting documentation.
Partner with senior analysts, subject matter experts, and cross-functional stakeholders to refine problem statements, validate findings, and support business decisions.
Ensure analytical accuracy by validating outputs, checking aggregation logic, and reconciling results where needed.
Manage multiple assignments and deliver timely, high-quality work in a fast-paced environment.