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High brand, mid-level generalist data role, metro location and broad skillset increase candidate competition.
Medium because core data engineering skills transfer, but retirement/wealth domain expertise increases specificity.
High due to explicit 5+ years and mandatory Python, SQL, ETL and domain experience requirements.
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Lead analytical workstreams end-to-end including requirements gathering, delivery, and stakeholder presentations across client engagements in data analytics and AI.
Design and develop complex data pipelines, ETL processes, and AI-enabled analytical models using Python, SQL, and cloud technologies like Databricks.
Coach and mentor junior team members while identifying opportunities to automate and improve delivery through reusable assets and AI-assisted approaches.
5+ years of experience in data analytics, data engineering, AI, or related technology disciplines.
Advanced proficiency in Python and SQL, including data engineering and automation.
Experience with Agile methodologies (Scrum, Jira, Confluence) and tools like SSIS, SSRS, Visual Basic.
Flexible to work in shifts and onsite at GGN / Noida office at least three days a week (hybrid model).
Experience leading small cross-functional workstreams involving multiple stakeholders in technical and business roles.
Strong practical experience applying modern AI techniques including GenAI, machine learning, and AI-assisted development for business outcomes.
Comfortable working in a retirement/wealth management domain or similar regulated financial services environment (preferred but not strictly mandatory).