Data Quality Analyst

Brown & Brown; United States; On-site; USD 80,000 - 95,000; Full time

Benefits offered by this job

Health benefits

401k/ESPP

Mental health services

Paid time off

Job summary

Brown & Brown's Arrowhead Intermediaries seeks a Data Quality Analyst to own data quality, integrity, and governance across reporting, analytics, and ML applications. You will define what good data means, build validation logic, controls, and investigations with the Data Strategy and BI teams.

You’ll apply statistical methods, trace discrepancies to root causes, and communicate fixes to both technical and non-technical stakeholders, supporting data-driven decision making.

Qualifications

• Experience with Python/R and SQL for data profiling, cleaning, and validation.
• Familiarity with statistical analysis: hypothesis framing, exploratory data analysis, interpretation of uncertainty
• Exposure to machine learning concepts and an understanding of how model output is evaluated for quality and consistency
• Demonstrated experience designing data validation rules, reconciliation processes, or quality controls across multiple systems of record
• Strong root-cause investigation skills, comfortable tracing data discrepancy from symptom to source
• A systems mindset: able to see how data flows across upstream sources, pipelines, and downstream consumers, and to spot where a fix in one place will surface problems in another
• A first-principles approach to problem-solving: able to break an unfamiliar or ambiguous data quality issue down to its underlying causes rather than relying on standard playbooks
• Comfortable working closely with engineering teams, whether that means partnering on pipeline changes, scoping a fix at its source, or translating a data quality issue into something an engineer can act on
• Visualization and communication skills (Matplotlib, ggplot, and/or Power BI) to make findings accessible to non-technical audiences
• Experience with AI tooling and LLM-based workflows (e.g., Claude, GPT) is important

Responsibilities

• Design and maintain validation rules, reconciliation processes, and quality checks across systems of record
• Investigate data integrity issues, tracing discrepancies between platforms and systems back to root cause
• Build and maintain data pipelines and profiling workflows in Python/R and SQL to support cleaning, structuring, and validation of incoming data
• Partner with data engineering and BI teams to define review and approval controls for data entering reporting and analytics pipelines
• Apply statistical methods (descriptive and inferential) to detect anomalies, quantify data quality issues, and support root cause analysis
• Evaluate the behavior and output of machine learning or scoring models against real-world outcomes, flagging drift or inconsistency
• Translate data quality findings into clear, actionable reporting for non-technical decision-makers and leadership
• Collaborate with stakeholders to define data quality metrics, standards, and reporting cadences across the Data Strategy and Business Intelligence organization

Skills

Python

R

SQL

Statistical analysis

Root-cause analysis

Data validation

Data governance

Visualization

AI tooling

Education

Data science background

Analytics background

Formal training in data science

Tools

Matplotlib

ggplot

Power BI

Job description

Built on meritocracy, our unique company culture rewards self-starters and those who are committed to doing what is best for our customers.

About The Role

Arrowhead Intermediaries is looking for a Data Quality Analyst to join our Data Strategy and Business Intelligence organization. This role sits at the intersection of statistical rigor and data governance: you'll own the quality, integrity, and reliability of the data that powers our reporting, analytics, and downstream machine learning applications. You'll work closely with the Director of Data Products to define what “good data” means for our systems, then build the validation logic, controls, and investigative processes to enforce it.

This is a great fit for someone who thinks like an analyst but cares as much about why the numbers are wrong as what the numbers say, someone comfortable owning a data quality question end to end: framing it, tracing it to root cause, and communicating the fix to both technical and non-technical stakeholders. Difficult data quality problems rarely have an off-the-shelf fix. We need someone who can reason from first principles: questioning assumptions about how the data was generated, tracing a discrepancy back to its source system, and building a systematic validation approach.

What You'll Do

• Design and maintain validation rules, reconciliation processes, and quality checks across systems of record
• Investigate data integrity issues, tracing discrepancies between platforms and systems back to root cause
• Build and maintain data pipelines and profiling workflows in Python/R and SQL to support cleaning, structuring, and validation of incoming data
• Partner with data engineering and BI teams to define review and approval controls for data entering reporting and analytics pipelines
• Apply statistical methods (descriptive and inferential) to detect anomalies, quantify data quality issues, and support root cause analysis
• Evaluate the behavior and output of machine learning or scoring models against real-world outcomes, flagging drift or inconsistency
• Translate data quality findings into clear, actionable reporting for non-technical decision-makers and leadership
• Collaborate with stakeholders to define data quality metrics, standards, and reporting cadences across the Data Strategy and Business Intelligence organization

What We\'re Looking For

• Experience with Python/R and SQL for data profiling, cleaning, and validation
• Familiarity with statistical analysis: hypothesis framing, exploratory data analysis, interpretation of uncertainty
• Exposure to machine learning concepts and an understanding of how model output is evaluated for quality and consistency
• Demonstrated experience designing data validation rules, reconciliation processes, or quality controls across multiple systems of record
• Strong root-cause investigation skills, comfortable tracing data discrepancy from symptom to source
• A systems mindset: able to see how data flows across upstream sources, pipelines, and downstream consumers, and to spot where a fix in one place will surface problems in another
• A first-principles approach to problem-solving: able to break an unfamiliar or ambiguous data quality issue down to its underlying causes rather than relying on standard playbooks
• Comfortable working closely with engineering teams, whether that means partnering on pipeline changes, scoping a fix at its source, or translating a data quality issue into something an engineer can act on
• Visualization and communication skills (Matplotlib, ggplot, and/or Power BI) to make findings accessible to non-technical audiences
• Experience with AI tooling and LLM-based workflows (e.g., Claude, GPT) is important

A background in data science, analytics, or a related field, formal training or eq

Pay Range

$80,000.00 - $95,000.00 Annual

The pay range provided above is made in good faith and based on our lowest and highest annual salary or hourly rate paid for the role and takes into account years of experience required, geography, and/or budget for the role.

Teammate Benefits & Total Well-Being

• Health Benefits: Medical/Rx, Dental, Vision, Life Insurance, Disability Insurance
• Financial Benefits: ESPP; 401k; Student Loan Assistance; Tuition Reimbursement
• Mental Health & Wellness: Free Mental Health & Enhanced Advocacy Services
• Beyond Benefits: Paid Time Off, Holidays, Preferred Partner Discounts and more.

Not reflective of all benefits. Enrollment waiting periods or eligibility criteria may apply to certain benefits. Benefit details and offerings may vary for subsidiary entities or in specific geographic locations.

Recruiting Vendor Disclosure Statement

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As an Equal Opportunity Employer, we are committed to fostering an inclusive environment comprised of people from all backgrounds, with a variety of experiences and perspectives, guided by our Diversity, Inclusion & Belonging (DIB) motto, “The Power to Be Yourself”.