Senior Data Analyst - Insight & Gap Navigator

Quantum Technologies. LLC

Tampa (FL)

On-site

USD 120,000 - 160,000

Full time

14 hours ago

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Job summary

Quantum Technologies LLC in Tampa, FL is seeking a senior Data Analytics Lead to partner with business stakeholders, define critical questions, and evaluate whether current data can answer them. You will identify gaps, drive plans with data engineers, and design dashboards turning raw data into actionable insights.

The ideal candidate has 10+ years in data analytics, strong SQL, Python or R, and experience building dashboards in Tableau or Power BI.

Qualifications

10+ years of experience in data analysis, business intelligence, or analytics, including direct client-facing or cross-functional stakeholder work.
Proven track record of identifying data gaps and driving cross-team efforts to resolve them, not just working with whatever data is handed over.
Strong SQL skills and hands-on experience with at least one scripting/analysis language (Python or R).
Experience building dashboards and reports in a modern BI tool (Tableau, Power BI, or similar).
Solid grounding in data modeling, data quality assessment, and data lineage concepts.
Demonstrated ability to communicate technical findings to non-technical business and executive audiences.
Bachelor's degree in a quantitative field (statistics, computer science, engineering, mathematics, or related); equivalent practical experience considered.

Responsibilities

Partner with business stakeholders to define the questions that matter, then assess whether current data can actually answer them.
Identify gaps between the data that's available and the data that's needed — in coverage, granularity, quality, or timeliness — and document the specific impact of each gap.
Drive the plan to close those gaps: working with data engineering, IT, and business-side data owners to source, capture, or correct the missing data.
Design and build analyses, dashboards, and reports that turn raw and newly sourced data into clear, decision-ready insight.
Validate data quality and lineage before analysis ships, and flag where conclusions should be caveated.
Translate findings for non-technical stakeholders and leadership, with a clear narrative of what the data shows and what it still can't.
Establish repeatable processes and documentation so data gaps are caught earlier next time, not just patched after the fact.
Mentor junior analysts on both technical analysis and the discipline of questioning data completeness.