Project overview: This project focuses on enhancing data analytics and business intelligence capabilities using modern data engineering tools and cloud-based data platforms. You will contribute to building reliable data pipelines, improving data models, and enabling advanced analytics to support informed business decisions.
Position overview: We are looking for a Data Engineer with hands on experience in modern data stack technologies. You will be responsible for developing scalable data workflows, building and optimizing data models, and working closely with analytics and business teams to deliver actionable insights.
Technology stack: Snowflake, dbt, Looker, Python, SQL, cloud platforms

• Responsibilities: Develop, maintain, and optimize data pipelines and ETL and ELT processes using Snowflake and dbt
• Design and implement scalable data models to support analytics and reporting needs
• Create and maintain dashboards and data explorations in Looker
• Write clean and efficient Python scripts for data processing, automation, and integrations
• Collaborate with data analysts, data scientists, and business users to gather and refine data requirements
• Ensure data quality, consistency, and reliability across platforms
• Monitor and troubleshoot data workflows and performance issues
• Participate in code reviews, documentation, and knowledge sharing within the team

• 2 to 4 years of professional experience as a Data Engineer or in a similar role
• Hands on experience with Snowflake data warehouse
• Experience with Looker
• Proficiency in dbt for data transformation and modeling
• Experience building dashboards and reports using Looker
• Strong programming skills in Python for data processing and automation
• Solid knowledge of SQL and relational databases
• Familiarity with data pipeline orchestration and workflow management tools
• Strong analytical and problem solving skills
• Ability to communicate effectively and collaborate within a team

• Nice to have: Experience with cloud platforms such as AWS, GCP, or Azure
• Knowledge of data governance, security, and compliance practices
• Familiarity with containerization and CI CD pipelines for data workflows