Senior Data Analyst – AI & Snowflake Cortex
Experience
5–6 years in Data Analytics / AI‑driven Analytics roles
Location
Pune (hybrid)
Role Summary
We are looking for a Senior Data Analyst with strong AI and Snowflake expertise to build intelligent, scalable, and business‑ready analytics solutions.
The role will focus on advanced analytics, AI‑assisted insights, ML‑enabled data products, and agentic analytics using Snowflake Cortex AI, working closely with product, engineering, and business stakeholders.
Key Responsibilities
Data Analytics & Business Insights
- Translate complex business problems into data‑driven analytics solutions using Snowflake and BI tools.
- Design and deliver self‑service analytics, semantic models, and metrics aligned to enterprise KPIs.
- Perform exploratory data analysis (EDA) and advanced SQL analytics on large, complex datasets.
Snowflake & Data Engineering (ETL/ELT)
- Build and optimise ETL / ELT pipelines into Snowflake from enterprise systems (Salesforce, ERP, marketing platforms, etc.).
- Implement data modelling (dimensional / analytical models) optimised for analytics and AI consumption.
- Ensure data quality, performance, cost optimisation, and governance within Snowflake.
AI, ML & Snowflake Cortex AI
- Implement Snowflake Cortex AI capabilities, including:
- Text‑to‑SQL / natural language analytics (Cortex Analyst)
- AI functions such as classify, extract, summarise, and translate
- Partner with data science teams to deploy ML models in Snowflake for:
- Predictive analytics
- Forecasting and anomaly detection
- Intelligent scoring and recommendations
- Operationalise ML models using Snowflake ML, feature stores, and model lifecycle best practices.
Agentic & LLM‑Driven Analytics
- Design and implement LLM‑powered and agentic analytics use cases, such as:
- Conversational analytics and AI assistants
- Automated insight generation
- Intelligent data validation and reconciliation
- Integrate LLMs (OpenAI / Azure OpenAI / Snowflake Cortex LLMs) with governed enterprise data.
- Apply RAG patterns responsibly, ensuring accuracy, security, and explainability.
Data Governance & Security
- Implement role‑based access control (RBAC), data masking, and row‑level security in Snowflake.
- Ensure AI solutions comply with enterprise data governance and privacy standards, with all data processed within Snowflake’s boundary.
Stakeholder Collaboration
- Work closely with product owners, business teams, and AI/ML engineers to define analytics requirements.
- Present insights clearly to leadership through dashboards, narratives, and AI‑generated summaries.
Required Skills & Qualifications
Core Technical Skills
- 5–6 years of experience in Data Analytics / Advanced Analytics
- Strong hands‑on expertise in Snowflake (SQL, performance tuning, data modelling)
- Experience building ETL/ELT pipelines (ADF, dbt, or similar tools)
- Advanced SQL and solid Python for analytics and ML integration
AI / ML / LLM Skills
- Working experience with Snowflake Cortex AI or similar AI‑assisted analytics platforms
- Understanding of LLMs, prompt engineering, RAG patterns, and agentic workflows
- Hands‑on experience with ML models (classification, regression, forecasting, anomaly detection)
- Familiarity with ML lifecycle, model monitoring, and explainability
BI & Visualisation
- Experience with Power BI / Tableau / Streamlit
- Ability to design executive‑ready dashboards and self‑service analytics experiences
Nice to Have
- Experience with Streamlit apps inside Snowflake
- Exposure to Salesforce, ERP, marketing, or supply chain analytics
- Build ML models for prediction, scoring, forecasting, anomaly detection
- Operationalise models using Snowflake ML / feature stores / registries
- Design RAG pipelines using governed enterprise data
- Develop conversational analytics assistants and AI insight engines
- Ensure explainability, security, and governance of AI solutionsAgile delivery experience in enterprise data platforms
