Senior Analytics / Business Intelligence Engineer
Product & Experimentation Analytics | Analytics Engineering | Applied AI (Foundations)
📍 Hyderabad, India

I’m a Senior Analytics / BI Engineer with a strong product mindset, focused on building decision-grade analytics systems that leaders trust and use.

I’ve owned analytics end-to-end across large-scale B2B eCommerce (Dell Technologies) and enterprise finance & regulatory analytics (HCLTech), working closely with product, engineering, and business stakeholders. My work emphasizes metric correctness, experimentation, and scalable analytics foundations—not just dashboards.

I also support AI- and ML-powered product features through analytics, experimentation, and evaluation, ensuring these systems deliver measurable business impact and remain reliable in production environments.

• Analytics Engineering

  • SQL-first modeling, fact–dimension design, semantic layers
  • Governed metrics and single source of truth
  • Scalable analytics foundations used for leadership decisions

• Product & Experimentation Analytics

  • A/B testing, funnel & UX analysis
  • Hypothesis-driven evaluation of product features
  • Translating experiment results into clear go / no-go decisions

• Metrics & Decision Ownership

  • KPI definition and metric standardization
  • Reducing reconciliation, improving trust in analytics
  • Partnering with leaders on recurring business decisions

• Applied AI (Foundations)

  • Evaluating ML/AI features using metrics and experimentation
  • Business-safe AI thinking: reliability, usefulness, guardrails
  • Treating AI as a product capability, not a one-off model

End-to-end analytics engineering demonstrating production-ready patterns

• Built analytics-ready fact & dimension models
• Centralized KPI definitions to eliminate metric drift
• Designed semantic layers optimized for BI consumption
• Reduced downstream BI complexity and improved query performance

Business outcome:
Improved metric consistency and enabled faster, trusted decision-making.

Tech: SQL · dbt-style modeling · Snowflake-style warehousing · Power BI · Python
🔗 https://github.com/balaji27venkatesh-AI/portfolio-analytics-engineering

Experimentation-driven product analytics for confident decision-making

• Defined hypotheses and success metrics before launch
• Analyzed A/B tests and funnel behavior using SQL & Python
• Balanced statistical significance with business impact
• Delivered clear product recommendations based on evidence

Business outcome:
Enabled confident product decisions and avoided shipping low-impact features.

Tech: Python · SQL · A/B Testing · Funnel Analysis · Statistics
🔗 https://github.com/balaji27venkatesh-AI/portfolio-product-analytics-experimentation

System-oriented applied AI design with business safety in mind

• Designed AI interactions aligned to business intent
• Focused on evaluation, reliability, and controlled behavior
• Treated AI as a product feature with measurable outcomes

Business outcome:
Improved consistency and trust in AI-assisted decision workflows.

Tech: Python · LLMs · Prompt & System Design · Evaluation Frameworks
🔗 https://github.com/balaji27venkatesh-AI/portfolio-applied-ai-business-assistant

• Dell Technologies — Senior Business Intelligence Engineer

  • Revenue analytics driving +6pp YoY online revenue mix
  • A/B experimentation supporting ML features contributing $10M+ revenue
  • UX & operational analytics improving conversion and CSAT

• HCLTech — Lead Analytics Engineer

  • Finance metrics standardization reducing reconciliation by ~90%
  • Regulatory analytics platform reducing reporting cycle from ~8 weeks to ~1 week

✅ Senior / Staff Analytics Engineer - Building scalable analytics infrastructure
✅ Product Analytics Lead - Experimentation and product-driven insights
✅ AI / Analytics Engineer (Applied AI) - Owning AI-powered product features

Preferred Setup: Product-based teams in Hyderabad (office/hybrid) where analytics and AI directly drive measurable business outcomes

Current focus areas:

• Advanced analytics engineering patterns (incremental models, snapshots, testing)
• Evaluation-first thinking for AI systems (reliability, usefulness, guardrails)
• Foundations of LLM-based systems (prompt design, retrieval concepts)
• Understanding modern data orchestration patterns (conceptual)

📚 My Learning Journey - DSML foundations and hands-on projects

• 💼 LinkedIn: linkedin.com/in/balaji27venkatesh
• 📧 Email: balaji27venkatesh@gmail.com
• 🎥 YouTube: @balaji27venkatesh-YT
• 📷 Instagram: @balaji_27_venkatesh
• 🐦 X: @balaji_279

“The goal of analytics isn’t dashboards — it’s better decisions, faster.”

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