Data Analyst

Responsibilities :

• Core Analytics -
• Respond promptly to data requests from diverse teams and stakeholders, using AI-assisted workflows to reduce turnaround time.
• Analyze and interpret complex datasets to extract meaningful, decision-ready insights.
• Develop and maintain interactive dashboards (Tableau / Metabase / Power BI) that clearly communicate KPIs and trends.
• Utilize SQL for efficient data extraction, transformation, and analysis—including AI-assisted query generation, optimization, and debugging.
• Employ advanced Excel / Google Sheets functionalities for data manipulation.
• Data Infrastructure & Quality (Familiarity Level) -
• Understand and monitor existing ETL pipelines to ensure data is syncing correctly from source databases (RDS/MySQL, Elasticsearch, etc.) into the data warehouse.
• Keep an eye on pipeline health, identify job failures, and work with the technical team to ensure data freshness for reporting.
• Write and run optimized queries on Amazon Redshift, with a basic understanding of how data warehouse tables are structured for performance.
• Maintain data quality through regular reconciliation checks between source systems and final reporting tables.
• AI-Augmented Working -
• Leverage AI assistants (Claude, Gemini, etc.) to accelerate SQL writing, data cleaning, exploratory analysis, and report drafting.
• Write effective prompts and build reusable AI workflows/templates for recurring analysis and reporting tasks.
• Automate repetitive reporting and data operations using scripts (Python / Apps Script) — with or without AI assistance.
• Critically validate AI-generated outputs: verify logic, check numbers against source data, and catch hallucinations before anything reaches stakeholders.
• Follow data privacy and security best practices when using AI tools — never expose sensitive or client data to unapproved platforms.
• Stay current with emerging AI/analytics tools and proactively suggest ways to improve team productivity.
• Collaboration & Communication -