Back
Strong employer brand plus metro location but senior, specialized role yields medium competition.
High because mandatory finance domain knowledge and regulated reporting experience limit cross-industry transferability.
High due to explicit 10+ years, mandatory finance domain expertise, and specialized GenAI/Snowflake requirements.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead design, development, and implementation of enterprise-scale data platforms including data warehousing, reporting, analytics, and AI-powered data solutions.
Drive integration of GenAI, LLMs, and AI/ML for automation, natural language data interaction, RAG architectures, and agent-based AI solutions primarily on cloud platforms like Snowflake.
Provide technical leadership, mentor data engineering teams, and collaborate with stakeholders to define data and AI strategies aligned with business goals.
Minimum 10 years of experience in data engineering or related roles; at least 6 years in relevant skills for this role.
Deep expertise in SQL, data modeling, ETL, and scalable data pipelines using cloud platforms, preferably Snowflake.
Strong domain knowledge in finance, investment banking or related industries and demonstrated experience implementing AI/GenAI enterprise solutions including RAG and LLM orchestration.
Experience with AI governance, model risk, security, privacy, responsible AI controls, and modern agile SDLC practices; Work Experience Required: 10+ years in data engineering, 6+ years relevant AI experience.
Experienced leader capable of managing large-scale finance technology data engineering and AI teams in regulated environments.
Proven track record in architecting AI-powered natural language and agentic data interaction solutions using modern cloud platforms.
Strong collaborator able to work with diverse stakeholders to define and execute enterprise data and AI strategies with governance and evaluation frameworks.