In order to be considered for this role, after clicking "Apply Now" above and being redirected, you must fully complete the application process on the follow-up screen.Overview
The
Data Engineer IV will help lead the long-term effort to make data workflows proprietary, scalable, and margin-effective. This person builds the pipelines, models, and standards that let us own that work ourselves, rely less on outside vendors and services, and give the business faster, more reliable answers.
This role pays an annual salary of $135,000-$170,000
Benefits for Full-Time roles: Health, Dental and Vision Insurance, 401(k) Savings Plan, 401(k) matching, and Paid Time Off (vacation days, sick days, and 11 holidays)This position will remain open until November 20, 2026.Responsibilities
Infrastructure & Pipelines- Build and maintain the ETL/ELT pipelines connecting CRM, Outreach, Salesforce Marketing Cloud, ticketing, web analytics, advertising platforms, reporting tools, and the data lake
- Take on recurring data movement and integration work that's currently being outsourced to agencies
- Keep infrastructure scalable, reliable, and secure as data volume and system count grow
Data Modeling, Governance & Quality- Build and maintain the data models and warehouse structures that reporting and analytics run on
- Own data cleansing, validation, and quality checks so people trust the numbers they're looking at
- Work with the VP, Revenue Systems & Data to set architecture, governance, and documentation standards
Analytics & Data Science- Enhance lead score modeling and drive client adoption
- Build out statistical models and predictive analytics that improve sales and marketing performance
- Analyze data to adapt or reconstruct business processes
- Implement the use of AI where there is direct ROI to KPIs
Team & Cross-Functional Work- Manage the Marketing and Sales Analysts, making sure their reporting is built on clean data
- Partner with CRM & Systems, Revenue Marketing, and Sales Performance so infrastructure decisions match what those teams need, and speed up turnaround on ad hoc requests
Qualifications
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field.
- 6+ years of experience in data engineering, enterprise data architecture, or analytics engineering.
- Strong hands-on experience with SQL, data modeling, ETL/ELT development, APIs, and cloud-based data platforms.
- Demonstrated experience building scalable data infrastructure supporting CRM, marketing automation, business intelligence, and reporting environments.
- Strong understanding of data governance, data quality, security, metadata management, and master data management best practices.
- Experience developing predictive analytics, statistical models, machine learning, or AI-driven solutions to improve business performance.
- Proven ability to integrate data across multiple platforms such as CRM systems, marketing automation platforms, web analytics, advertising platforms, and third-party applications.
- Experience leading or mentoring analysts, engineers, or technical teams while effectively managing cross-functional projects and stakeholder relationships.
- Excellent analytical, problem-solving, communication, and documentation skills with the ability to translate business requirements into scalable technical solutions.
