Data Visualization Specialist

This is a fully remote position, open to applicants in India.

📋 Description

• Create and develop scalable, low-latency dashboards that pull data from data warehouses (such as Snowflake, Redshift, and BigQuery) as well as real-time data streams (like Kafka and Kinesis).

• Design AI-enhanced visualization layers that display outputs from machine learning models, including churn prediction scores, lifetime value forecasts, behavioral clustering, and anomaly detection signals.

• Implement semantic data layers and metric definitions using tools like dbt or LookML to maintain consistency across reporting.

• Build natural language interfaces on top of dashboards utilizing LLMs (for example, OpenAI APIs and AWS Bedrock), allowing business users to query data in a conversational manner.

• Create automated insight generation systems that summarize trends, pinpoint anomalies, and suggest actions through NLP/LLMs.

• Enhance dashboard performance by employing efficient query designs, caching strategies, and incremental data models.

• Integrate visualization tools with backend APIs and machine learning services to facilitate dynamic, real-time updates.

• Collaborate with ML Engineers to interpret model outputs and design visualization patterns that accurately represent uncertainty, confidence intervals, and predictions.

• Establish data governance practices that include lineage tracking, metric validation, and monitoring.

⛳️ Requirements

• Advanced expertise in BI tools (Power BI, Tableau, Looker) with a background in embedding dashboards and customizing through APIs.

• Strong SQL skills with experience in optimizing complex queries over large-scale datasets (in the billions of rows).

• Experience with modern data stacks: Warehouses including Snowflake, Redshift, and BigQuery; Transformation using dbt; Streaming technologies like Kafka and Kinesis.

• Familiarity with Python for data manipulation (using tools like pandas and NumPy) and light backend integration.

• Knowledge of machine learning outputs and statistical concepts (such as classification, regression, clustering, and anomaly detection).

• Experience with integrating LLMs/NLP pipelines into reporting workflows.

• Understanding of data modeling (star/snowflake schemas) and performance optimization techniques.

• Experience with API integrations and embedding analytics into internal platforms.

🏝️ Benefits

• Competitive salary along with performance-based incentives.

• Access to a vibrant, international, and rapidly growing environment.

• Strong opportunities for career advancement within a global financial group.