Lead Data Engineer

Prana Tree is a fast-growing IT consulting and product innovation firm specializing in AI, DataEngineering, Blockchain, and Cloud solutions.

We are seeking an experienced Lead Data Engineer to design, build, and lead scalable data platforms and pipelines. The ideal candidate will have strong hands-on expertise in Snowflake, DBT, and Apache Airflow , along with the ability to mentor teams and drive best practices across data engineering initiatives.

• Lead the design and development of scalable, high-performance data pipelines and data platforms.
• Architect and optimize Snowflake-based data warehouses , including schema design, performance tuning, and cost optimization.
• Develop and maintain DBT models to support reliable, modular, and well-documented data transformations.
• Orchestrate and monitor data workflows using Apache Airflow , ensuring reliability and fault tolerance.
• Establish and enforce data engineering best practices , coding standards, and CI/CD processes.
• Mentor and guide junior and mid-level data engineers.
• Collaborate with product, analytics, and business teams to translate requirements into technical solutions.
• Ensure data quality, lineage, governance, and security across platforms.
• Support production deployments, troubleshooting, and performance optimization.

• 8+ years of experience in Data Engineering, including a leadership or lead role.
• Strong hands-on expertise in:
• Snowflake (data modeling, performance tuning, cost optimization)
• DBT (data transformations, testing, documentation)
• Apache Airflow (workflow orchestration and monitoring)
• Advanced proficiency in SQL and strong programming skills in Python .
• Experience with cloud platforms (AWS, Azure, or GCP ).
• Solid understanding of data architecture, ETL/ELT patterns, and modern data stack concepts.
• Experience implementing data quality checks, monitoring, and alerting.
• Strong communication, leadership, and stakeholder management skills.

• Experience with streaming data technologies (Kafka, Kinesis, Pub/Sub).
• Familiarity with DevOps/MLOps tools such as Docker, CI/CD pipelines, and Infrastructure as Code.
• Prior experience in agile delivery environments .

• Bachelors or Masters degree in Computer Science , Data Engineering , Information Systems , or a related field.