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Data Operations Analyst

About DataVue

DataVue is a consumer credit intelligence company that provides credit data and analytics to lenders nationwide. We work with comprehensive credit bureau data, national mortgage and deed records, demographic files, and specialty datasets—processing multi-terabyte databases with hundreds of millions of consumer records to help our clients build smarter marketing campaigns.

The Role

This is a hands-on SQL execution role. You’ll be the person who turns client campaign specifications into precise data extractions from our multi-terabyte consumer credit database. Every order has specific selection parameters, suppression logic, and filtering criteria (ML score deciles, debt thresholds, geographic targeting, etc.) that need to be translated into performant queries against tables with 200M+ rows.

Think of it as order fulfillment through SQL: clients define who they want to reach, you build the query, apply the business logic, validate the output, and deliver clean, accurate data. Speed and precision matter—our clients depend on getting the right audience for every campaign.

What You’ll Do

Write and execute complex SQL queries to extract targeted consumer populations from our database based on client-defined selection parameters
Apply suppression files, exclusion logic, and layered selection criteria (e.g., top X machine learning score deciles, average debt ranges, geographic filters, etc.) to refine extractions
Process inbound client files—response data, conversion files, suppression lists—and integrate them into modeling and campaign workflows
Run feasibility counts and exploratory analysis for sales and strategy teams to scope new opportunities
Prepare and validate input datasets for response modeling workflows
Maintain deep, working knowledge of the data dictionary: attribute definitions, derived vs. raw fields, dependencies, constraints, and known edge cases
Optimize query performance against large-scale tables; identify and resolve bottlenecks
Document queries, data definitions, and recurring campaign logic for operational consistency
Generate reports on list sizes, audience characteristics, and data quality metrics
Collaborate with client-facing teams to translate campaign objectives into precise technical requirements

Required

3–6 years of experience in a SQL-heavy analyst, data operations, or analytics engineering role
Advanced SQL skills (4+yrs) —complex joins, subqueries, window functions, CTEs, query optimization. This is not a role where SQL is one of many tools; it’s the primary tool
Hands-on experience with large-scale databases (100M+ records) and multi-table schemas with real performance considerations
Ability to translate business requirements into precise, efficient queries without hand-holding
Strong attention to data quality and accuracy—you catch your own mistakes before they ship
Excel excellence for ad hoc analysis, pivot tables, and data validation

Nice to Have

Experience with consumer credit data, financial services, or direct marketing data
Familiarity with response modeling concepts and how data feeds ML workflows
Python for data manipulation and automation
C# experience
Exposure to big data tools or cloud-based query engines (Spark, Athena, etc.)
AWS infrastructure/architecture

Where This Role Goes

This is an immediate, execution-focused need—but it’s not a dead end. DataVue is actively building out its ML and data infrastructure capabilities, and this role sits right at the center of that data. Strong performers will have a clear path into response modeling, data engineering, and analytics architecture as the team grows.

This role is for someone who thinks in SQL, thrives on precision, and wants to see the direct business impact of every query they write. If you’re looking for a role where your technical skills drive revenue from day one, we want to hear from you.

Job Type: Full-time

Pay: $80,000.00 - $100,000.00 per year

Benefits: