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Data Visualization Engineer information
See Atlanta, GA salary details
$42.8K - $54.4K
0% of jobs
$54.4K - $66K
1% of jobs
$66K - $77.7K
3% of jobs
$77.7K - $89.3K
4% of jobs
$89.3K - $100.9K
7% of jobs
$111.1K is the 25th percentile. Wages below this are outliers.
$100.9K - $112.6K
11% of jobs
$112.6K - $124.2K
12% of jobs
The median wage is $127.3K / yr.
$124.2K - $135.8K
45% of jobs
$135.8K - $147.4K
8% of jobs
$147.4K - $159.1K
5% of jobs
$159.1K - $170.7K
3% of jobs
$42.8K
$124.7K
$170.7K
How much do data visualization engineer jobs pay per year?
What is a Data Visualization Engineer job?
A Data Visualization Engineer is responsible for designing, developing, and implementing visual representations of data to help stakeholders understand complex information. They use tools like Tableau, D3.js, Power BI, and Python libraries (e.g., Matplotlib, Seaborn) to create interactive dashboards and reports. Their role involves working with large datasets, ensuring data accuracy, optimizing performance, and collaborating with analysts and developers to enhance decision-making. Strong programming, data analysis, and UX/UI design skills are essential for success in this role.
What are some common challenges faced by Data Visualization Engineers, and how can they overcome them?
Data Visualization Engineers often encounter challenges such as translating complex data into clear, actionable visuals for non-technical stakeholders and ensuring that graphics remain both accurate and engaging. Balancing the needs of different departments, adhering to fluctuating project requirements, and managing large or messy datasets can also be demanding. Successful engineers address these issues by working closely with data analysts, business users, and designers, using feedback to iterate on their work, and staying current with the latest visualization best practices. Proactive communication and strong organization skills further help in meeting deadlines and maintaining quality standards.
What are the key skills and qualifications needed to thrive in the Data Visualization Engineer position, and why are they important?
To thrive as a Data Visualization Engineer, you need a strong grasp of data analysis, visual storytelling, and programming, often supported by a degree in computer science, data science, or a related field. Familiarity with tools like Tableau, Power BI, D3.js, and proficiency in languages such as Python or JavaScript are commonly required, along with experience in databases and dashboard development. Strong communication, problem-solving, and collaboration skills help you effectively transform and present complex data to diverse audiences. These abilities are crucial for creating impactful, user-friendly visualizations that drive informed business decisions.
Full-time
Posted 6 days ago
Job description
- Analyze large and complex datasets to identify trends, insights, and business opportunities within the payment domain.
- Develop, optimize, and maintain data pipelines to support business intelligence and analytics.
- Work extensively with Aurora DB (MySQL/PostgreSQL) for data modeling, querying, and performance tuning.
- Design and implement scalable data architectures, ensuring data integrity and security.
- Collaborate with data analysts, software engineers, and business teams to define data-driven solutions.
- Implement machine learning models to enhance fraud detection, transaction analytics, and customer behavior analysis.
- Automate data ingestion, transformation, and storage processes using ETL frameworks.
- Utilize cloud platforms (AWS, GCP, or Azure) for data engineering and storage solutions.
- Monitor data quality, identify anomalies, and improve data accuracy.
- Stay updated on industry trends, particularly in payments domains, fintech, and emerging data technologies.
Required Skills:
- 3-6 years of experience as a Data Engineer/Data Scientist, preferably in the payment domain industry.
- Strong expertise in Aurora DB (MySQL/PostgreSQL) schema design, indexing, query optimization, and performance tuning.
- Proficiency in SQL and database management.
- Hands-on experience with Python, R, or Scala for data processing and analysis.
- Experience with ETL frameworks and data pipeline development.
- Familiarity with Big Data technologies (e.g., Spark, Hadoop, Kafka) is a plus.
- Cloud experience in AWS, GCP, or Azure, particularly in data storage and processing.
- Strong analytical and problem-solving skills with experience in predictive modeling and statistical analysis.
- Knowledge of fraud detection, transaction processing, or risk analytics in payments is highly desirable.
- Experience working with data visualization tools (e.g., Tableau, Power BI) is a plus.
- Ability to communicate insights and recommendations to stakeholders effectively.
Preferred:
- Certifications in AWS Data Engineering, Big Data, or Machine Learning are a plus.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. NLB is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. To request reasonable accommodation, contact HR department by sending an e-mail to notifications@nlbservices.com.
About NLB Services
Sourced by ZipRecruiter
Industry
Recruiting and staffing services
Company size
10,000+ Employees
Headquarters location
Alpharetta, GA, US
Year founded
2007