Data Analyst

About VIMO:

Vimo started as the “Expedia” of health insurance and has evolved into a leader in transforming government IT infrastructure with its proven SaaS and AI technology. Our innovative approach to health insurance shopping and enrollment has expanded beyond exchanges, and we are now reinventing how states administer safety net programs such as Medicaid, SNAP (food stamps), child care, and unemployment insurance.

With our cutting-edge technology, we are helping agencies serve more people, faster, and transforming healthcare service delivery as we know it.

We are looking for a detail-oriented Data Analyst to own the integrity, flow, and delivery of data across our reporting ecosystem — with a particular focus on call center operations. You will serve as the connective tissue between source systems, data pipelines, and BI platforms, ensuring that reports are accurate, timely, and meaningful to the teams that rely on them. This role is equal parts investigator, data steward, and reporting partner.

Responsibilities:

Monitor, validate, and maintain data flows from call center platforms (e.g., Nice CxOne, Five9, Genesys, Avaya) through ETL/ELT pipelines into the data warehouse and BI layer

Triage and resolve data discrepancies, reporting anomalies, and integration issues across systems — owning the problem through to root cause and fixMap how call center data (call volumes, handle time, CSAT, agent metrics) joins with data from CRM, workforce management, ticketing, and financial systems

Build and maintain documentation for data dictionaries, field mappings, and transformation logic

Partner with engineering and platform teams to surface pipeline failures, schema changes, or upstream data quality issues before they reach end-users

Develop and sustain dashboards and reports in BI tools (e.g., Sisense, Tableau, Power BI) that consolidate cross-system metrics into operational views

Conduct ad hoc analysis to support operations, finance, and workforce planning teams

Define and monitor data quality checks and alerting for key reporting metrics

Communicate data nuances and known limitations to business stakeholders clearly and proactively

Compensation and Benefits:

Competitive compensation - Please note that salary and compensation may vary based on factors such as skills, experience, performance and location.

We offer a comprehensive benefits package, including but not limited to:
Health, Dental, Life, Disability, and Vision insurance

Healthcare spending or reimbursement accounts (HSA/FSA)
Retirement benefits (401k)
Paid time off Holidays: 13 paid days per year Education assistance or tuition reimbursement-Employee discounts for Gym memberships & commuting/travel assistance

Our Vaues:

We believe that working hard, when it is imbued with purpose, can and should be fun.

You’ll find we are a “can do” place where people work together and roll up their sleeves to get the job done.

Everyone has a voice; everyone’s ideas count, and everyone is respected.

We have built a company, as well as a community of friends and colleagues, with respect for each other.

Information Security & Data Protection:

This role may involve access to sensitive or regulated information. The candidate is expected to handle all data in accordance with company security, privacy, and data protection policies.

Compliance with access control, data classification, and applicable legal and regulatory requirements is required.

Basic Qualifications:

5+ years of experience Data Analysis or related fields

Proficient SQL — complex joins, CTEs, window functions, query optimization

Hands-on experience with BI platforms (Tableau, Power BI, Looker, or similar)
Familiarity with ETL/ELT tools or data pipelines (dbt, Fivetran, Airflow, or similar)
Experience working with call center or contact center data Strong analytical thinking and attention to data detail

Ability to communicate technical findings to non-technical stakeholders

Preferred Qualifications:

Python or R for data wrangling and automation

Experience with cloud data warehouses (Snowflake, Big Query, Redshift)
Knowledge of call center KPIs: AHT, FCR, ASA, CSAT, NPSFamiliarity with data governance or cataloguing tools

Experience with CRM data and WFM systems

Background in operations analytics or workforce management

What Success Looks Like:

Reporting issues are identified and resolved before stakeholders notice them

Call center and cross-system data is reliably consolidated and consistently defined

Dashboards reflect a single source of truth that operations and leadership trust

Data flow documentation is thorough enough for anyone on the team to follow
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