10+ years of experience in data analysis, business intelligence, or analytics with client-facing roles
Proven ability to identify and resolve data gaps across teams
Strong SQL skills and experience with Python or R
Experience with modern BI tools like Tableau or Power BI
Solid understanding of data modeling, quality assessment, and lineage
Ability to communicate technical findings to non-technical audiences
Bachelor's degree in a quantitative field or equivalent experience
Responsibilities
Partner with stakeholders to define critical business questions and assess data availability
Identify and document gaps in data coverage, quality, and timeliness
Drive initiatives to source and correct missing data with cross-functional teams
Design and build analyses, dashboards, and reports for decision-making
Validate data quality before analysis and flag limitations in findings
Translate complex data insights for non-technical stakeholders
Establish processes to catch data gaps early and mentor junior analysts
Benefits
Flexible work location in Dallas, TX or Tampa, FL
Opportunity to mentor junior analysts
Engagement in cross-functional collaboration
Access to modern BI tools and technologies
Involvement in impactful data-driven decision-making
Full Job Description
Role description
Location: Dallas, TX Or Tampa, FL Role Summary:
We're hiring a Senior Data Analyst who does more than report on the data that already exists. Our clients and internal teams regularly hit a wall where the data needed to answer a real business question is incomplete, siloed, or simply not being captured yet. This role exists to close that gap: spotting where data is missing or unreliable, working with source system owners and data engineering to get it captured or corrected, and then turning it into analysis that actually drives a decision. You will operate as much as a data detective and problem-solver as a traditional analyst - comfortable saying "here's what the data can't tell us yet, and here's how we get there."
Key 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
Required 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
Preferred Qualifications:
Experience in IT services or consulting, where data sits across multiple client systems and ownership boundaries
Domain exposure to BFSI & Regulated Data
Familiarity with cloud data platforms (Snowflake, Azure, AWS, or GCP) and modern ELT/ETL tooling
Exposure to AI/ML-assisted analytics or working alongside data science teams
Experience standing up data governance or data quality frameworks from scratch
