Data Analyst (Python & BI Tools)

What will you do?

Analytics & KPI Design

• Partner with marketing and business teams to define, validate, and finalize KPI frameworks, including stage-wise performance metrics.
• Translate high-level business objectives into measurable analytics models aligned with operational efficiency and campaign performance.

Data Analysis & Insights

• Perform historical, trend, and variance analysis using Python and SQL to identify productivity drivers, bottlenecks, and inefficiencies.
• Conduct root cause analysis on SLA breaches, workflow delays, and high-duration process stages.
• Develop data-backed recommendations to improve workforce utilization, throughput, and campaign outcomes.

Reporting & Dashboarding

• Design, build, and maintain interactive Power BI dashboards using DAX, drill-downs, filters, and KPI visualizations.
• Integrate dashboards with Excel Power Query models for near real-time reporting and automated data refresh.
• Create Excel-based prototype reports to validate business logic and metric definitions before production rollout.

Automation & Data Engineering

• Build and automate ETL and data preparation pipelines using Python and SQL.
• Reduce manual reporting effort through workflow automation, reusable data models, and standardized processes.
• Ensure data accuracy, consistency, and scalability across all analytics and reporting solutions.

Stakeholder Collaboration

• Collaborate cross-functionally with analytics, marketing, operations, and leadership teams.
• Communicate insights clearly to non-technical stakeholders through dashboards, reports, and presentations.
• Own KPI definitions, logic validation, documentation, and ongoing metric governance.

What will you need?

Technical Skills

• Python (Pandas, NumPy; exposure to Scikit-learn is a plus).
• SQL including complex joins, query optimization, and performance tuning.
• Power BI (DAX, interactive dashboards, KPI reporting).
• Advanced Excel Power Query, Pivot Models, data modeling.
• Strong understanding of data modeling, data cleaning, and ETL concepts.

Analytical Skills

• KPI design, metric validation, and performance measurement.
• Root cause analysis and structured problem-solving.
• Data storytelling and insight-driven communication.

Education

• Bachelors degree in Engineering, Analytics, Statistics, Computer Science, or a related field.
• Masters degree in Business Analytics or Data Analytics preferred.