Design and implement enterprise-scale data pipelines and analytics platforms that transform raw data into strategic insights
Create executive-level dashboards and reports that drive strategic business decisions
Lead cross-functional analytics projects from requirements gathering through deployment, managing stakeholder expectations and leading end to end delivery
Partner with Product Owners, Data Scientists, and senior leadership to align analytics initiatives with business strategy
Design and maintain enterprise data models and data warehouses that scale with organizational growth
Optimize complex SQL queries and implement efficient ETL/ELT processes for large-scale data processing
Develop production-ready Python/Pyspark/SQL code for advanced analytics & automation
Develop advanced analytical models including predictive analytics, segmentation, and optimization algorithms for business growth
Architect cloud-based analytical solutions on Azure, optimizing for performance and cost efficiency
OTHER ACCOUNTABILITIES (Secondary Responsibilities)
Implement data governance frameworks including quality standards, documentation, and compliance requirements
Present complex analytical findings to non-technical executives and business stakeholders
Stay current with industry trends and introduce new analytics technologies and methodologies
Contribute to product roadmap decisions based on data-driven insights and market analysis
Facilitate analytics community of practice sessions and knowledge sharing initiatives
Collaborate with IT architecture teams on technical standards and infrastructure decisions
Qualifications, Experience And Skills
B.E./B.Tech in Computer Science, IT, or related field;
3-8 years of experience in data analytics, business intelligence, or related fields
Strong analytical thinking and ability to interpret complex datasets.
Strong verbal and written communication skills - able to simplify and present insights.
Expert-level SQL skills including stored procedures, performance tuning, and complex data modelling
Hands-on experience with cloud platforms (Azure Data Factory, Databricks, AWS, or GCP equivalents)
Proficiency in advanced Excel and ability to visualize datasets
Advanced Python programming with pandas, numpy, scikit-learn, and production deployment experience (Good to have)
Experience with Power BI, including DAX, custom visuals, and enterprise deployment (Good to have)
Experience with big data technologies (Spark)
Proven track record of leading analytics projects and mentoring technical teams
