Data Visualization Engineer at Suzuki Digital · Gurugram · 2 - 4 years · ₹4L - ₹12L / yr · Profitable · Posted 12 Mar 2025

Hi
Job Title: Data Visualization Engineer
Experience: 2 to 4 years
Location: Gurgaon (Hybrid)
Employment Type: Full-time
Job Description:
We are seeking a skilled Data Visualization Engineer with expertise in Qlik Sense and experience working with reporting tools like PowerBI, Tableau, Looker, and Qlik Sense. The ideal candidate will have a strong understanding of QVF and QVD structures, basic HTTP API integrations, and end-to-end data pipelines. Some knowledge of Python for data processing and automation will be a plus. This role will primarily focus on Qlik Sense reporting.
Key Responsibilities:
1. Data Visualization & Reporting
- Design, develop, and maintain interactive dashboards and reports using Qlik Sense.
- Work with PowerBI, Tableau, Looker, and Qlik Sense to create compelling data visualizations.
- Ensure seamless data representation and storytelling through dashboards.
2. Qlik Sense Development & Optimization
- Develop and manage QVF and QVD structures for optimized data retrieval.
- Implement best practices in Qlik Sense scripting, data modeling, and performance tuning.
- Maintain and optimize existing Qlik Sense applications.
3. Data Integration & API Interactions
- Utilize basic HTTP APIs to integrate external data sources into dashboards.
- Work with data teams to ensure smooth data ingestion and transformation for visualization.
4. End-to-End Data Pipeline Understanding
- Collaborate with data engineers to understand and optimize data flows from source to visualization.
- Ensure data consistency, integrity, and performance in reporting solutions.
5. Scripting & Automation
- Utilize Python for data manipulation, automation, and minor custom integrations.
- Improve reporting workflows through automation scripts and process optimizations.
Technical Expertise Required:
- 2 to 4 years of experience in Data Visualization or BI Reporting roles.
- Strong experience with Qlik Sense (QVF & QVD structures, scripting, visualization).
- Hands-on experience with PowerBI, Tableau, Looker.
- Basic understanding of HTTP APIs for data integration.
- Understanding of end-to-end data pipelines.
- Knowledge of Python for automation and data transformation.
- Experience in performance optimization of dashboards and reports.
- Strong analytical and problem-solving skills.
Preferred Qualifications:
- Experience in data modeling and ETL concepts.
- Familiarity with cloud-based data visualization solutions.
- Understanding of data governance and security best practices.

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- Experience combining data from multiple software systems, databases, APIs, files, or vendor platforms.
- Experience with sensor, machine, equipment, IoT, or time-series data.
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- Python or R
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- Data validation and data-quality analysis
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- Power BI, Tableau, QuickSight, or a comparable BI platform
- Cloud data lakes or cloud analytics environments
- Relational and non-relational data sources
- Advanced Microsoft Excel
- Predictive modeling or machine learning
- API or multi-system data integration
Specific experience with every listed technology is not required. The candidate must, however, have strong foundational analytics skills and the ability to learn unfamiliar platforms and data environments.
Critical Competencies
- Analytical curiosity
- Structured problem-solving
- Systems thinking
- Data accuracy and attention to detail
- Continuous-improvement mindset
- Business and operational awareness
- Clear written and verbal communication
- Cross-functional collaboration
- Client responsiveness
- Adaptability and willingness to learn
- Ability to convert analysis into action
Experience
Approximately 4 to 8 years of relevant professional experience is preferred. Candidates with fewer years may be considered if they demonstrate strong hands-on analytics experience, manufacturing exposure, and the ability to work directly with engineering and operational stakeholders.
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The successful candidate will:
- Create trusted and repeatable manufacturing datasets.
- Deliver dashboards and reports that stakeholders actively use.
- Identify meaningful risks, trends, and improvement opportunities.
- Help engineering and operations teams make better decisions from their data.
- Improve the consistency of tool-specific information across systems.
- Progressively develop more advanced predictive and AI-enabled Digital Mold capabilities.
- Produce measurable improvements in reliability, operational performance, cost, and efficiency.
Suggested Key Skills
Data Science, Manufacturing Analytics, Data Analytics, Business Intelligence, Dashboard Development, Data Visualization, Power BI, Tableau, Amazon QuickSight, SQL, Python, R, Statistical Analysis, Data Cleansing, Data Normalization, Data Validation, Data Quality, Manufacturing KPI, OEE, MTTR, MTBF, Predictive Analytics, Machine Learning, Continuous Improvement, Process Optimization, Maintenance Analytics, Reliability Analytics, Cloud Data Lake, Sensor Data, IoT Analytics, Injection Molding, Plastics Manufacturing












