Data Support Analyst

Data Support Analyst

We are seeking a Data Support Analyst to support day-to-day data operations across our enterprise data environment. This role is ideal for a technically skilled professional with experience troubleshooting data issues, supporting business users, and collaborating with data engineering teams. The primary focus of this role is managing and resolving data-related tickets, including investigating discrepancies, validating data, and coordinating resolutions with business and technical teams. In addition, the analyst will provide ad-hoc support to the Data Engineering team by assisting with pipeline monitoring, data validation, file transfers, and operational tasks across our Azure-based data platform. Hybrid Work Environment: This role can be based in our Washington, DC or Bloomington, MN office. We believe collaboration drives innovation, so team members work together in the office four days per week, with one day each week working remotely.

Responsibilities and Duties:

Data Ticket Support

• Serve as the primary point of contact for data-related incidents, requests, and inquiries submitted through ServiceNow.
• Investigate and resolve data discrepancies, missing records, reporting issues, and other operational data problems.
• Work directly with business users to gather requirements, clarify issues, and communicate resolution status.
• Document troubleshooting steps, resolutions, and recurring issue patterns to improve support processes and knowledge sharing.
• Escalate complex issues to the Data Engineering team when root cause analysis indicates a pipeline, integration, or platform-level problem.

Data Operations & Quality Support

• Perform routine data validation and quality checks to ensure accuracy, completeness, and consistency across key business datasets.
• Assist in identifying recurring data quality issues and recommend process improvements or upstream controls.
• Support monitoring of scheduled data loads and notify the appropriate teams of failures or anomalies.
• Help maintain operational documentation, runbooks, and support procedures for common data issues.

Ad-Hoc Data Engineering Support

• Assist the Data Engineering team with operational tasks such as validating data loads, reviewing pipeline outputs, and troubleshooting minor ETL issues.
• Support secure file transfer (SFTP) processes and vendor data delivery workflows.
• Help test and validate changes to data pipelines, reports, and integrations before deployment.
• Participate in ad-hoc projects related to data cleanup, reporting support, and process automation.
• Collaborate with engineers and analysts to ensure timely resolution of data-related production issues.

Collaboration & Communication

• Act as a liaison between business teams, IT support, analytics, and data engineering.
• Translate business data into actionable technical investigations.
• Provide clear, professional communication regarding ticket status, findings, and next steps.
• Contribute to continuous improvement efforts for data support workflows and service delivery.

Education and Experience:

• Bachelor's degree in Information Systems, Computer Science, Business Analytics, or a related field preferred.
• Equivalent combination of experience, coursework, or technical certifications may be considered in lieu of a degree.
• 2–5 years of experience in data support, business systems support, reporting support, or a related technical role.
• Experience working with ticketing systems such as ServiceNow strongly preferred.

Required Technical Skills

• Strong SQL skills for querying, validating, and troubleshooting data issues.
• Experience with ServiceNow incident/request management workflows.
• Familiarity with relational databases such as SQL Server.
• Understanding of ETL/data pipeline concepts and enterprise data flows.
• Proficiency with Microsoft Excel and basic data analysis techniques.
• Strong troubleshooting and problem-solving skills

Preferred Skills

• Exposure to Azure Data Factory (ADF) and/or Databricks.
• Experience with SFTP processes and file-based data exchanges.
• Basic knowledge of Python or scripting for automation and data validation.
• Experience supporting reporting or business intelligence environments.
• Familiarity with data quality and monitoring practices.

Key Competencies:

• Data Analysis & Troubleshooting: Investigates data discrepancies, identifies root causes, and resolves data-related issues with accuracy and efficiency.
• SQL & Data Validation: Utilizes SQL and data validation techniques to ensure data integrity, accuracy, and consistency across enterprise systems.
• Technical Support & Service Management: Provides responsive support through ServiceNow, managing incidents and requests while delivering excellent customer service.
• Data Operations & Quality Management: Monitors data pipelines, validates data loads, and supports ongoing data quality and operational reliability.
• Cross Functional Collaboration: Partners effectively with business users, Data Engineering, IT, and Analytics teams to resolve issues and improve data processes.
• Process Improvement & Documentation: Maintains support documentation, identifies recurring issues, and recommends process enhancements that improve efficiency and service delivery.

How This Role Demonstrates Our Values:

• Integrity: Ensures the accuracy, reliability, and security of enterprise data while following established support and governance practices.
• Collaboration: Works closely with business partners, Data Engineering, IT, and Analytics teams to resolve issues and support business operations.
• Excellence: Delivers timely, high quality data support, maintains strong service levels, and contributes to reliable data operations.
• Critical Curiosity: Investigates root causes, identifies opportunities for automation and process improvement, and continuously expands technical knowledge to enhance data support capabilities.

Benefits

• Competitive compensation package, including base salary and performance-based bonus opportunities
• 401(k) plan with 100% company match up to 4%
• Comprehensive health coverage: medical, dental, vision, HSA, and FSA options
• Generous paid time off: 20 days PTO, company holidays, and sick time
• Paid parental leave
• Company-paid life insurance and disability coverage
• Employee Assistance Program (EAP): mental health, financial, and wellness support
• Professional development: tuition reimbursement and growth opportunities
• Commuter and transit benefits

Successful applicants will exemplify strong ethics, integrity, respect for others, accountability for decisions and actions, and good citizenship. Maintaining a reliable, uninterrupted high speed internet connection is a requirement of hybrid or remote positions. All job duties and responsibilities must be performed within the guidelines of the Verus Residential Mortgage Employee Handbook and established company policies and procedures. It is the responsibility of each employee to maintain confidentiality of the company, its clients and to follow applicable laws and regulations in the performance of duties. Verus Mortgage Capital is an equal opportunity employer. All qualified applicants are welcomed to apply and will receive consideration for employment without unlawful discrimination because of a person's race, religious creed, color, national origin, citizenship status, ancestry, marital status, sex, age, or sexual orientation, or because of a person's disability or medical condition.

About Invictus Capital Partners / Verus Mortgage Capital

Verus Mortgage Capital is an independent national mortgage investor. Verus offers its Sellers responsible non-prime and Jumbo prime lending products that fill the credit void in today's market. Verus consistently evaluates today's market and credible borrower financing needs to offer our partners innovative solutions. Verus Mortgage Capital is an affiliate of Invictus Capital Partners please visit our website at

Our Hiring Process

Stage 5:

Interview

Stage 6:

Offer

Stage 7:

Hired

Stage 1:

Applied

Stage 2:

HR Interview

Stage 3:

Assessment

Stage 4:

Review