Data Analytics Lead || Mumbai (WFO)

Job description

Location

Experience

Job Summary

Key Responsibilities

• Develop and execute the strategic roadmap for the Data & Analytics and AI/ML practice
• Lead data consulting and delivery engagements, including data platform implementations, BI/reporting solutions, and advanced analytics (Predictive analytics, NLP, computer vision, generative AI)
• Build and manage a high-performing team of data engineers, analysts, architects, and data scientists
• Guide clients through data modernization, cloud migration, governance, and analytics initiatives
• Define delivery methodologies, standards, frameworks, and best practices
• Collaborate with sales/pre-sales teams to craft winning proposals and provide solution architecture support
• Stay updated on the latest trends in big data, AI/ML, cloud analytics, and data governance
• Establish partnerships with technology vendors (e.g., Microsoft, AWS, Snowflake, Databricks)
• Lead capability building, mentoring, and internal knowledge development within the practice

• Required Qualifications

• Bachelors or Masters degree in Computer Science, Data Science, Engineering, or related field
• 8+ years of experience in data and analytics, with at least 3 years in a leadership role
• Proven track record of managing large-scale data projects, teams, and client relationships
• Expertise in data warehousing, ETL, big data platforms, cloud analytics (AWS, Azure, or GCP), and modern BI tools (Power BI, Tableau, etc.)
• Strong understanding of data governance, data quality, metadata management, and compliance
• Hands-on experience with Python and ML libraries/frameworks (TensorFlow, PyTorch, Scikit-learn, Hugging Face, etc.)
• Experience with MLOps, model lifecycle management, and cloud-based ML platforms
• Proven track record of leading AI projects from ideation to production deployment
• Excellent communication, stakeholder engagement, and team-building skills

Preferred Skills

• Experience in data science or machine learning (Python, R, ML pipelines)
• Hands-on knowledge of modern data platforms (Snowflake, Databricks, Synapse, BigQuery, etc.) and Generative AI (LLMs, diffusion models, prompt engineering)
• Familiarity with industry-specific data models (e.g., healthcare, BFSI, retail) and ethical AI principles, fairness, and explainability (XAI)
• Certifications in Azure Data, AWS Big Data, Google Cloud Professional Data Engineer, etc. including AI/ML tracks
• Experience working in consulting, R&D, or product-focused AI environments
• Publications, patents, or participation in open-source AI/ML projects

Thanks & Regards

Akanksha Gupta|

HR Associate-Talent Acquisition

akanksha.gupta@rigvedit.com