Job Description

Role Purpose & Overview

The primary purpose of this role is to architect, build, and optimize innovative data solutions by leveraging advanced Snowflake technologies integrated with cutting-edge AI capabilities. The individual will be responsible for designing, developing, and debugging models, simulations, and data workflows that align precisely with the client’s and project requirements, ensuring seamless data operations within complex enterprise environments.

In this position, you will engage deeply with Snowflake’s latest AI-empowered tools, including Snowflake CoCo, CoWork, and Cortex, to accelerate developer productivity and automate business processes. The role demands a blend of expert technical skills, a proactive approach to continuous learning, and collaborative problem-solving capabilities to deliver scalable, efficient data solutions that power business insights.

Key Contributions Include:

• Developing and enhancing scalable data pipelines, performing robust data modeling and warehousing on the Snowflake Data Cloud platform to support complex analytics and reporting needs.
• Employing Snowflake CoCo to facilitate AI-driven SQL query generation, automate routine data engineering tasks, and optimize workflows for peak developer productivity.
• Utilizing Snowflake CoWork to implement AI-powered workflow automation, streamline reporting procedures, and generate actionable business insights through sophisticated AI agents.
• Exploring and applying Snowflake Cortex and Snowpark capabilities to harness prompt-engineered data querying, AI/ML analytics, and innovative use case developments.
• Collaborating with cross-functional teams and stakeholders to comprehensively translate evolving business requirements into effective, agile data solutions.
• Leading initiatives for performance tuning, cost efficiency, and governance compliance within Snowflake environments to ensure optimal platform utilization and security.
• Championing AI adoption by integrating predictive analytics, automation strategies, and intelligent reporting within enterprise data platforms.

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Responsibilities and Expectations

• Architect, develop, and maintain end-to-end data solutions within the Snowflake ecosystem, ensuring alignment with best practices and project timelines.
• Leverage AI capabilities within Snowflake products (CoCo, CoWork, Cortex) to automate data workflows, enhance developer efficiency, and assist in complex SQL query generation and optimization.
• Design and implement automated reporting systems and AI-powered business analysis tools to accelerate data-driven decision making.
• Work closely with technical and business stakeholders to gather requirements, troubleshoot issues, and iterate on solutions to maximize business value.
• Ensure stringent data governance, security compliance, and regulatory adherence as part of solution design and operation.
• Drive continuous improvement by participating in code reviews, skill development activities, and championing innovative AI use cases within data engineering domains.
• Maintain clear and proactive communication channels to manage expectations, address challenges, and share status updates effectively across teams.
• Support skill certification efforts and actively engage in learning to stay current with Snowflake platform advancements and AI technologies.

Required Technical Expertise

• 3 to 8 years of professional experience in Snowflake development, particularly in data engineering, data modeling, and ETL/ELT processes.
• Proficiency in Snowflake's AI ecosystem: hands-on experience with Snowflake CoCo (developer assistant), CoWork (AI agents for operations), and Cortex for AI-driven querying and analysis.
• Strong command of SQL writing and performance tuning, with familiarity working across leading cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Demonstrated understanding of generative AI concepts and practical skills in prompt engineering to enable effective AI interactions within data workflows.
• Experience scripting with Python or similar languages for automating data engineering tasks is highly valued.
• Ability to analyze complex data problems, apply innovative solutions, and optimize workflows for efficiency and accuracy.

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Deliverables and Performance Metrics

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Core Competencies

• Client Centricity: Demonstrates a commitment to understanding and fulfilling client needs by delivering tailored, high-quality data solutions.
• Passion for Results: Exhibits a strong drive to achieve goals and meet deadlines, ensuring impactful outcomes aligned with business objectives.
• Execution Excellence: Maintains high standards of work quality, timely delivery, and process adherence across all projects and tasks.
• Collaborative Working: Engages effectively within multidisciplinary teams, fostering a culture of knowledge sharing, openness, and mutual support.
• Learning Agility: Shows eagerness in continual learning and skill development, adapting to emerging technologies and industry trends with agility.
• Problem Solving & Decision Making: Applies critical thinking to analyze challenges, evaluate options, and implement effective solutions responsibly and efficiently.
• Effective Communication: Articulates ideas clearly and listens actively, ensuring transparent and constructive exchanges with peers, stakeholders, and clients.

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Preferred Qualifications and Additional Skills

• Professional Snowflake certifications such as SnowPro Core or Advanced certifications add significant value and demonstrate validated expertise.
• Domain experience within Banking, Financial Services, Insurance (BFSI), Payments, or Treasury operations provides beneficial contextual knowledge for specific data solutions and regulatory needs.
• Familiarity with data governance frameworks, security protocols, and regulatory compliance standards ensures alignment with organizational risk management requirements.
• Hands-on experience with Python or similar scripting languages to automate complex data processing pipelines enhances efficiency and reliability.
• Exposure to agentic AI tools and implementing AI-driven enterprise workflows showcases forward-thinking adaptability in emerging AI ecosystems.
• A solid understanding of Artificial General Intelligence (AGI) concepts broadens capacity to innovate and contribute to next-generation AI-enabled data platforms.

Soft Skills

• Excellent interpersonal and communication skills to manage diverse stakeholder groups and foster productive collaboration.
• A proactive and self-motivated attitude with a strong inclination towards driving innovation and embracing AI transformation initiatives.
• Capable of balancing technical depth with business awareness to deliver solutions that are both effective and aligned with strategic goals.