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Frontend Data Visualization Jobs in Memphis, TN (NOW HIRING)

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Frontend Data Visualization information

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$59.3K

$135K

$192.4K

How much do frontend data visualization jobs pay per year?

As of Aug 6, 2026, the average yearly pay for frontend data visualization in Memphis, TN is $134,968.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,800.00 and $156,900.00 per year, depending on experience, location, and employer.

What is a frontend data visualization specialist?

A Frontend Data Visualization specialist is a professional who designs, develops, and implements interactive visual representations of data using web technologies. They combine skills in frontend development—such as HTML, CSS, and JavaScript—with expertise in data visualization libraries like D3.js, Chart.js, or Plotly. Their role is to turn complex data sets into intuitive, visually engaging charts, graphs, and dashboards that help users understand and analyze information. They often collaborate with data analysts, UX/UI designers, and backend developers to ensure data is accurately and effectively presented. Frontend Data Visualization specialists are essential in making data-driven insights accessible and actionable for a wide range of audiences.

What are the key skills and qualifications needed to thrive as a frontend data visualization specialist, and why are they important?

To thrive as a Frontend Data Visualization specialist, you need strong proficiency in JavaScript, HTML, CSS, and libraries like D3.js or Chart.js, often supported by a degree in computer science or a related field. Familiarity with data fetching APIs, version control systems like Git, and experience with visualization frameworks or tools (e.g., Tableau, Power BI) are typically required. Creativity, problem-solving, and the ability to communicate complex data insights visually are standout soft skills. These competencies are crucial for transforming raw data into compelling, interactive visuals that drive better decision-making and user engagement.

What are some common challenges faced by frontend data visualization professionals when collaborating with cross-functional teams?

Frontend Data Visualization professionals often work closely with data scientists, backend engineers, and product managers to create intuitive, interactive visual representations of complex data. A common challenge is ensuring that the visualizations accurately reflect the underlying data while remaining user-friendly and visually appealing. Effective communication is key, as translating technical data requirements into interactive UI components can involve balancing technical feasibility with user experience. Additionally, aligning on data freshness, performance, and responsive design standards often requires regular coordination across teams.
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Frontend Data Visualization jobs near you

Senior Full Stack Java Developer with Databricks

Zealogics

Memphis, TN • On-site

$46.75 - $60.50/hr

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Senior Full Stack Java Developer with Databricks

We are seeking a Senior Full Stack Java Developer with Databricks to design and develop a modern publication management system from the ground up. This role will contribute across the full technology stack, including user interfaces, APIs, business logic, and data engineering components, to deliver a scalable, intuitive, and maintainable platform supporting publication tracking, curation workflows, reporting, analytics, and integrations.

Key Responsibilities
  • Design and develop end-to-end features across frontend, backend, and data layers.
  • Build modern, responsive user interfaces for publication management and curation workflows.
  • Develop and maintain backend services, APIs, and business logic using Java and related technologies.
  • Design, develop, and optimize data processing pipelines using Databricks, Apache Spark, and Delta Lake.
  • Collaborate with architects to implement modern architectural patterns and design standards.
  • Translate business and user requirements into scalable technical solutions.
  • Implement data models and persistence for complex bibliographic and metadata-driven systems.
  • Develop and maintain ETL/ELT workflows for ingesting, transforming, and managing large volumes of publication and research data.
  • Integrate with internal and external systems, data sources, and third-party platforms.
  • Write clean, testable, and well-documented code.
  • Participate in code reviews and contribute to engineering best practices.
  • Troubleshoot, optimize, and improve application performance, data processing efficiency, and usability.
Required Skills & Experience

  • Proven experience as a Senior Full Stack Software Engineer on enterprise-scale applications.

  • Strong proficiency in:

    • Frontend: React (preferred), Angular, or Vue.js
    • Backend: Java (Spring Boot), REST APIs, Microservices
    • Data Engineering: Databricks, Apache Spark (PySpark/Spark SQL), Delta Lake

  • 3+ years of hands-on experience with Databricks in enterprise environments.

  • Experience designing, developing, and optimizing data pipelines and ETL/ELT processes using Databricks.

  • Strong experience working with Apache Spark, Delta Lake, Databricks Workflows, and Lakehouse Architecture.

  • Experience building and consuming RESTful APIs.

  • Solid understanding of modern software development practices, including:

    • Microservices-based architectures
    • API-first design
    • Agile development methodologies

  • Experience with relational and/or NoSQL databases and data modeling.

  • Experience integrating Databricks with cloud platforms such as Azure, AWS, or Google Cloud Platform.

  • Familiarity with cloud-native or hybrid deployment environments.

  • Strong understanding of data governance, data quality, performance tuning, and monitoring within Databricks environments.

  • Strong problem-solving skills and attention to detail.

  • Excellent communication and collaboration skills.

Preferred Qualifications
  • Experience with greenfield development and phased delivery models.
  • Familiarity with publication management systems and research information systems.
  • Knowledge of scholarly metadata standards such as DOI, ORCID, MeSH, PubMed, or similar.
  • Experience building dashboards, reports, analytics, or data visualization solutions.
  • Experience with Unity Catalog, Delta Live Tables (DLT), MLflow, and Databricks Lakehouse Platform.
  • Databricks Certification (Associate or Professional Data Engineer) is a plus.
  • Background in research, healthcare, academic, or life sciences environments.
Nice-to-Have
  • Exposure to AI/ML-assisted features, such as metadata enrichment, intelligent classification, or recommendation systems.
  • Experience with CI/CD pipelines, containerization, and DevOps tooling.
  • Understanding of security, accessibility, and data governance best practices.
What Success Looks Like
  • Delivery of intuitive, high-quality user interfaces, robust backend services, and scalable Databricks-based data solutions.
  • Well-architected, maintainable code and data pipelines supporting long-term scalability.
  • Strong collaboration with architects, analysts, data engineers, and stakeholders.
  • Contributions that measurably improve usability, efficiency, analytics capabilities, and system reliability.

Must-Have Technologies: Java, Spring Boot, React, Databricks, Apache Spark, SQL, REST APIs, Microservices, Cloud (Azure/AWS).

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