Lumiq.Ai - Snowflake Data Engineer

Location: Noida
Company:
Experience: 3–6Years (can be adjusted)

is a data-driven AI and analytics company focused on building scalable, intelligent solutions that help businesses make better decisions. We work with modern cloud data stacks and cutting-edge technologies to deliver high-impact analytics and AI products.

We are looking for a skilled Snowflake Data Engineer to design, build, and maintain scalable data pipelines and analytics solutions. The ideal candidate will have strong experience with Snowflake, Data Built Tools, Airflow, and SQL, and will play a key role in enabling reliable, high-quality data for analytics and AI use cases.

• Design, develop, and optimize data models and pipelines using Snowflake

• Build and maintain transformation workflows using DBT following analytics engineering best practices

• Orchestrate and schedule data pipelines using Apache Airflow

• Write efficient, optimized SQL queries for data transformation, validation, and analysis

• Ensure data quality, consistency, and reliability across data pipelines

• Collaborate with data scientists, analysts, and product teams to understand data requirements

• Implement performance tuning, cost optimization, and security best practices in Snowflake

• Maintain documentation for data models, pipelines, and processes

• Troubleshoot and resolve data pipeline and performance issues

• 3 years of experience as a Data Engineer

• Strong hands-on experience with Snowflake (schemas, warehouses, performance tuning)

• Solid experience with dbt (models, tests, macros, documentation)

• Experience with Apache Airflow for workflow orchestration

• Advanced SQL skills (complex joins, window functions, CTEs, optimization)

• Experience working with cloud platforms (AWS / Azure / GCP – preferred)

• Understanding of data warehousing concepts and dimensional modeling

• Experience with version control systems like Git

• Experience with Python for data engineering tasks

• Knowledge of CI/CD pipelines for data workflows

• Familiarity with data quality frameworks and monitoring tools

• Exposure to analytics or AI/ML data use cases

• Opportunity to work on modern cloud data stack and AI-driven projects

• Collaborative and fast-paced work environment

• Competitive compensation and benefits

• Learning and growth opportunities with cutting-edge technologies