Data Analyst

Key Responsibilities

• Team Leadership & Management
• Lead, mentor, and manage a small team of data analysts.
• Allocate tasks, monitor progress, and ensure timely delivery of analytics projects.
• Analytics & Business Insights
• Engage with stakeholders to understand analytics and reporting requirements.
• Translate business needs into data-driven solutions and dashboards.
• Business Intelligence (BI) & Visualization
• Develop, maintain, and optimize dashboards and reports using AWS QuickSight / Power BI /

Open-source tools / Open-source libraries.

• Design user-friendly and interactive visualizations tailored to business stakeholders.
• Explore and implement open-source BI tools for cost-effective solutions.
• ETL & Data Engineering
• Design, build, and manage ETL pipelines using AWS services (Glue, Lambda, Redshift, etc.).
• Ensure data quality, consistency, and reliability across analytics solutions.
• Adopt best practices in data architecture and pipeline optimization.
• Open-Source & Advanced Analytics
• Leverage open-source libraries (e.g., E charts, Plotly, etc.) for custom analytics solutions.
• Stay updated with emerging tools and frameworks in the data analytics ecosystem.

Required Skills & Qualifications

• 5+ years of proven experience as a Lead in data analytics, BI, and data pipeline development.
• Prior experience in leading/managing a small team.
• Strong proficiency in BI tools: AWS Quicksight and Power BI.
• Hands-on experience in building ETL pipelines with AWS tools (Glue, Lambda, Redshift, etc.).
• Proficiency in SQL and working with large datasets.
• Experience with open-source BI tools and data analysis libraries.
• Strong problem-solving, analytical, and communication skills.
• Ability to translate complex data into meaningful insights for non-technical stakeholders.
• Experience in cloud data warehouses (e.g., Amazon Redshift, Snowflake, BigQuery).
• Experience with data governance, security, and compliance best practices.
• Knowledge of machine learning frameworks and statistical analysis (nice-to-have).