Aparna K.
Data Engineering & Ai Manager @Mondelēz International
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WORK HISTORY
Data Engineering & Ai Manager @Mondelēz International
Mumbai, IN
Leading a 10-member cross-functional data engineering pod to architect and deliver RGM.AI — an end-to-end ML-powered Revenue Growth Management platform for the US market — projected to drive $100M+ in incremental revenue in FY 2025-26 through optimised pricing and promotional strategies.What I owned:→ End-to-end technical architecture and solution design for the RGM.AI data platform→ Translating open-ended executive business questions into structured data solutions, data requirements, and delivery plans→ Cross-functional alignment between data engineering, data science, and US senior business leadership→ Introduction of Generative AI to automate pipeline development and SQL query generation — reducing manual engineering effort and accelerating time-to-insight→ Building a high-performance team culture: sprint rituals, code-review standards, technical mentorship, and delivery accountabilityStack: Python · PySpark · SQL · Databricks · Azure · GenAI (LLM-based automation) · Airflow · Delta Lake · Power BI
EDUCATION
Birla Institute of Technology and Science, Pilani
Postgraduate Degree, Artificial Intelligence and Machine Learning
Lovely Professional University
Bachelor of Technology (B.Tech.), Computer Science
Deakin University
Master of Business Administration - MBA, Strategy and Leadership
SKILLS
ABOUT APARNA K.
I build data infrastructure that becomes a business advantage. Over 8.5 years across CPG, e-commerce, and financial services, I\'ve led the full arc of data engineering — from architecting terabyte-scale pipelines and driving AI adoption, to building and mentoring teams that ship with high standards and low noise. At Mondelez, I am leading a 10-member data engineering pod to enhance and commercialise RGM.AI — an ML-powered platform for revenue growth management projected to drive $100M+ in incremental revenue for the US Market. I introduced Generative AI to automate pipeline development and SQL generation, and partnered directly with data science and executive leadership to close the gap between business questions and production-grade data solutions. At Tata Neu, I migrated an entire streaming infrastructure from Azure Event Hubs to Confluent Kafka — 75% cost reduction, zero downtime. I architected a universal data ingestion framework processing TBs of data daily across multiple brands, and built an in-house Data Observability platform that gave the organisation real-time control over data costs, governance, and quality. I also delivered BI dashboards used directly by CXOs during the 2024 IPL campaigns. Earlier at DBS Bank, I built the ML decisioning model that reduced corporate loan approval from 3 days to 90 seconds. What I\'m known for: → Translating ambiguous business problems into scalable data architecture → Building teams that deliver — with technical rigour, clear roadmaps, and real accountability → Making GenAI and data intensive platforms land in production, not just in decks → Communicating complex data work clearly to executives and cross-functional partners I\'m actively open to Data Engineering Lead, AI Engineering Lead, and Data Platform Lead roles at data-driven technology companies. Let\'s connect if you\'re building something worth building.
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