Associate, Data Quality

Job Description : Associate, Data Quality

Location : Arlington, VA

Company: Nightingale Technology

About Us

Nightingale Technology is a healthcare technology startup venture focused on improving lives through patient care intelligence. Our founding R&D team has spent the last few years building a foundational architecture to revolutionize the space. We are now entering a critical growth phase, moving from R&D into private previews and preparing for a wider release.

We are looking for a key R&D team member to help lead our data engineering and productionizing efforts as we build atop our base architecture. You will be working with a modern, cutting-edge technology stack to solve complex data challenges.

The Role

We are seeking an Associate, Data Quality based in Arlington, VA. This role is not for the faint of heart—it requires a passion for precision given the range, complexity and velocity of the information sources we ingest.

You will be accountable for the quality of data—including completeness, normalization, reduction of noise, and elimination of duplication—across the user platform. You will work closely with Product and Engineering leadership to verify that the information displayed is rigorously cleaned and mapped, relaying requirements to the backend team to ensure high-fidelity data presentation.

Note: This is an industry-agnostic role. We are looking for smart, high-IQ data investigators and technical problem solvers who can apply their skills to a new domain.

Key Responsibilities

1. Data Normalization & Integrity

- Execute ongoing data review and normalization efforts across complex data sources.

- Manage data mapping efforts to ensure disparate records align with our internal data models.

- Identify anomalies in data ingestion and define the logic required to clean them.

- Make critical decisions regarding terminology frameworks and standardization.

2. Platform QA & Logic Verification

- Notification QA: Review platform notifications to ensure fields are properly formatted and the data presentation is professional and accurate.

- Noise Reduction: Identify and eliminate data duplication to prevent users from seeing repetitive or unnecessary alerts.

- Logic Investigation: Detect "silent failures" where data is present in the pipeline (e.g., a message arrives in the raw data bucket) but failed to result in the expected user notification.

3. Data Coverage Accountability

- Own the metrics regarding data completeness and coverage accountability.

- Track and report on Key Performance Indicators (KPIs), such as the percentage of records successfully retrieved vs. attempted.

- Analyze gaps in data coverage and propose strategies to ensure the platform captures the full scope of activity.

Who You Are

- A Data Investigator: You have a natural curiosity for digging into large datasets to find the "needle in the haystack." You don't just see a number; you question where it came from and why it might be wrong.

- Technically Proficient: You are comfortable wrangling data using SQL or other querying tools to validate your findings.

- Detail-Obsessed: You have the patience and precision to map complex data relationships and catch logic errors that others miss.

- Technical Communicator: You can identify a data error and clearly explain the logic fix required to a Software Engineer.

Qualifications

- Experience: 2+ years of experience in data analysis, quality assurance, or technical operations.

- Technical Skills: Strong SQL skills are required. Experience with Python or other scripting languages is a plus.

- Education: Bachelor's degree in a quantitative field (Math, Economics, Computer Science, Engineering) or equivalent practical experience.

- Location: Must be based in or willing to relocate to Arlington, VA.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.