Data Visualization Engineer || Only W2

Position: Data Visualization Engineer Duration: 12+ Months Location: Atlanta, GA (Day 1 Onsite) Key Responsibilities • Design, develop, test, deploy, and maintain executive, portfolio, and operational dashboards for application maintenance, technology health, security/compliance/risk, vulnerabilities, and developer productivity. • Create enterprise scorecards and KPI frameworks that translate complex operational, risk, engineering, and portfolio data into clear, actionable insights. • Build reporting solutions using approved enterprise visualization platforms such as Power BI, Tableau, MicroStrategy, or other approved Truist technologies. • Integrate and aggregate data from enterprise platforms including ServiceNow, Archer, PPM tools, SharePoint, Workday, Rally, Git repositories, vulnerability platforms, application inventory/CMDB sources, and other enterprise systems. • Develop real-time or near-real-time data acquisition patterns using REST APIs, Graph APIs, scheduled extracts, event-driven integrations, and governed ETL/ELT processes. • Design and support common reporting data stores and semantic models using AWS capabilities such as DynamoDB, PostgreSQL/Amazon RDS, S3, Lambda, API Gateway, and related services. • Partner with technology leaders, product owners, cybersecurity, risk, audit, PMO, and engineering teams to gather requirements, define metrics, socialize insights, and drive adoption. • Establish dashboard standards for usability, accessibility, metric definitions, data quality, governance, refresh cadence, and production support. • Leverage approved AI tools and AI-assisted analytics capabilities to make dashboards more intelligent through natural language Q&A, automated insights, anomaly detection, trend summaries, and recommendation prompts. • Provide ongoing support, troubleshooting, performance tuning, and enhancement of dashboards, data models, APIs, and reporting pipelines. Required Skills & Experience • 6–8 years of experience in data visualization, business intelligence, analytics engineering, reporting, or data product development within a large enterprise environment. • Strong hands-on experience with one or more enterprise BI platforms such as Power BI, Tableau, MicroStrategy, or comparable approved dashboarding tools. • Advanced SQL skills and practical experience designing data models, semantic layers, measures, calculated fields, and reusable reporting datasets. • Experience integrating data from enterprise/SaaS platforms using APIs, connectors, scheduled extracts, web services, JSON/XML, and governed data pipelines. • Experience working with relational and/or NoSQL data stores such as PostgreSQL, SQL Server, Oracle, Amazon RDS, DynamoDB, or equivalent platforms. • Understanding of AWS-based data and integration patterns including S3, Lambda, API Gateway, IAM/security concepts, RDS/PostgreSQL, DynamoDB, and cloud monitoring practices. • Experience defining KPIs, data quality rules, reconciliation checks, metric lineage, and dashboard governance for enterprise reporting solutions. • Strong analytical, troubleshooting, data storytelling, documentation, and stakeholder communication skills. • Ability to work in agile delivery teams and partner across business, technology, risk, cybersecurity, audit, and operations stakeholders. Good to Have • Experience with ServiceNow reporting/data models, CMDB, ITSM, ITOM, GRC/IRM, or enterprise workflow data. • Exposure to Archer, Rally, Workday, SharePoint, PPM platforms, vulnerability management platforms, GitLab/GitHub, CI/CD tools, or similar enterprise systems. • Experience building AI-enabled reporting experiences using approved tools such as Copilot, Power BI Copilot capabilities, natural language Q&A, automated narrative summaries, anomaly detection, or intelligent alerting. • Python, DAX, M, Power Query, JavaScript, or other scripting experience for data transformation, automation, and advanced analytics. • Knowledge of developer productivity frameworks such as DORA metrics, flow metrics, agile delivery metrics, backlog health, and engineering capacity analytics. • Experience with data cataloging, data lineage, role-based access controls, dashboard certification, and production support processes. • Familiarity with financial services, regulatory environments, audit readiness, control monitoring, risk management, and security/compliance reporting. Preferred Qualifications • Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, Statistics, Business Analytics, or a related field; equivalent practical experience will be considered. • Experience working in banking, financial services, or another highly regulated large enterprise. • BI platform certifications such as Power BI, Tableau, MicroStrategy, or equivalent are preferred. • AWS certification or demonstrated cloud data engineering experience is a plus. • Strong collaboration, consulting, and executive communication skills with the ability to influence metric adoption and reporting standards.