Job Title:  Data & AI Senior Engineer

Seeking a skilled Data Engineer to lead Snowflake-based solutions supporting AI and Data initiatives. This role drives scalable infrastructure, legacy data warehouse migration, and robust ETL/ELT pipelines.The ideal candidate will have hands-on experience implementing Snowflake Data Cloud, strong ETL/ELT capabilities, and a proven ability to collaborate with business stakeholders. The engineer ensures secure, high-performance architecture aligned with AI workflows, while enforcing governance, quality, and seamless integration across platforms.

Design Responsibilities:

• Analyse internally and externally sourced raw data to generate BI and Advanced Analytics datasets based on stakeholder requirements.
• Design scalable data pipelines to curate sourced data into the in-house data warehouse.
• Develop data marts to facilitate dataset consumption by business and IT stakeholders.
• Propose data model changes that align with in-house data warehouse standards.\
• Define and execute migration activities from legacy databases to the Snowflake-based data warehouse.
• Implement and manage Snowflake governance (access control, data security, usage monitoring).
• Support AI use cases through data preparation and integration.
• Collaborate with cross-functional teams to deliver data-driven solutions.

Engineering Responsibilities:

• Data Pipeline Development: Design and implement ETL/ELT processes for AI and ML models.
• Infrastructure Management: Select and manage cloud-based data storage solutions.
• Model Deployment Support: Prepare datasets and environments for training and deploying AI models.
• Real-Time Analytics: Handle unstructured data and support real-time data processing.
• AI-Specific Tools: Work with vector databases, LLM pipelines, and frameworks like TensorFlow or PyTorch.

Collaboration & Governance

• Collaborate with data scientists, ML engineers, and business stakeholders.
• Ensure data governance, security, and compliance.
• Monitor and optimise AI model performance.

REQUIREMENTS:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related quantitative discipline.
• 4–5 years of hands-on experience implementing Snowflake data cloud in a production environment.
• Strong expertise in ETL/ELT tools and frameworks (e.g., AWS Glue, dbt, Talend, Informatica).
• Experience with MLOps tools like MLflow, Docker, and LangChain.
• Proven experience in data warehouse migration and cloud data architecture.
• Solid understanding of data modelling, SQL, and BI/Analytics concepts.
• Experience working closely with business teams to deliver data solutions aligned with strategic goals.
• Familiarity with Snowflake governance best practices.
• Certified in SnowPro Data Engineer.
• Deep knowledge of Snowflake performance optimisation, governance, and security.
• Experience with cloud technologies such as AWS RDS, AWS Fargate, AWS S3 and Azure .
• Familiarity with PostgreSQL, MS SQL, and other relational databases.
• Strong programming skills in Python and/or Java.
• Understanding of LLMs, RAG pipelines, and generative AI deployment..
• Strong problem-solving and analytical thinking.
• Excellent communication and stakeholder engagement skills.
• Ability to work independently and manage multiple priorities.
• Proactive mindset with a focus on continuous improvement.