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Tier‑1 brand, metro location, mid-level generalist BI skills and AI requirements increase competitive density.
Core BI, SQL and data modeling skills transfer across industries, though fintech domain knowledge helps.
Explicit 2–4 years plus mandatory Hive, advanced SQL, Python and BI architecture skills make screening strict.
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Define and execute data consumption strategy across the organization to enable scalable business intelligence.
Monitor performance trends and collaborate with engineering and product teams to build scalable data models and integration of AI-powered BI applications.
Establish processes and best practices for data modeling, querying, consumption, and reporting; act as SME for analytics tech stack and unblock technical challenges.
2-4 years of experience in data analytics or BI engineering roles.
Advanced SQL and Big Data querying skills, with proficiency in Hive internals and query optimization.
Strong understanding of data architecture including data handling, modeling, and data flows.
Knowledge of AI integration and Python for data processing and pipelines.
Experienced in building data systems and solutions at scale within fast-growing organizations.
Capable of bridging technical BI requirements and product engineering to drive data-driven decision making.
Skilled in leveraging AI/LLMs to automate BI insights and improve analytics capabilities.