Senior Data Engineer - Snowflake, DBT

We are looking for a Senior Data Engineer with strong hands-on experience in Snowflake, DBT, Python, and SQL to design and build scalable, production-grade data platforms. This role will focus on developing reliable data pipelines, implementing modern ELT practices, and enabling analytics and AI-driven decision-making through well-modeled and governed datasets. The position requires deep technical ownership, strong architectural thinking, and the ability to drive best practices across the data engineering lifecycle.

• Design, develop, and maintain scalable data pipelines using Python and modern ELT frameworks.
• Build and manage robust data warehouse solutions on Snowflake, including schema design, data modeling, and performance optimization.
• Develop modular, tested, and documented data transformations using dbt.
• Implement best practices for analytics engineering, including version control, testing, lineage, and documentation.
• Write optimized and scalable SQL transformations supporting analytical and reporting workloads.
• Develop reusable ingestion frameworks and automation workflows using Python.
• Ensure high data reliability through monitoring, validation checks, and automated testing strategies.
• Optimize Snowflake performance through warehouse tuning, query optimization, and storage management.
• Collaborate with Data Analysts, Data Scientists, and Business stakeholders to translate business requirements into scalable data solutions.
• Implement data governance standards including access control, lineage tracking, and data quality frameworks.
• Support orchestration and scheduling of workflows using Airflow or similar orchestration tools.
• Troubleshoot production data issues and drive continuous improvements in platform stability and performance.
• Mentor junior engineers and contribute to defining data engineering standards and architecture.

• 6+ years of experience in Data Engineering roles.
• Strong hands-on expertise in Snowflake including:
  • Data warehousing concepts
  • Query optimization
  • Performance tuning
  • Cost optimization strategies
• Extensive experience with dbt (Data Build Tool) for transformation, testing, and documentation.
• Advanced proficiency in SQL for large-scale analytical processing.
• Strong programming skills in Python for data processing and automation.
• Solid understanding of ELT/ETL architecture, dimensional modeling, and modern data stack principles.
• Experience with workflow orchestration tools such as Apache Airflow.
• Experience implementing testing, monitoring, and data quality frameworks.
• Familiarity with CI/CD practices for data pipelines.
• Strong problem-solving ability and ownership mindset.
• Excellent stakeholder communication and collaboration skills.

• Experience working with cloud platforms (AWS / Azure / GCP).
• Exposure to data governance and metadata management tools.
• Experience supporting BI, advanced analytics, or ML workloads.
• Knowledge of data observability frameworks.
• Prior experience mentoring engineers or leading technical initiatives.