Lead Data Engineer

We are looking for a Lead Data Engineer to drive the development of modern data platform. This role will focus on building scalable and reliable data pipelines using tools like DBT
, Snowflake
, and Apache Airflow
, and will play a key part in shaping data architecture and strategy.

As a technical leader, you’ll work closely with cross-functional teams including analytics, product, and engineering to deliver clean, accessible, and trustworthy data for business decision-making and machine learning use cases.

• Lead the design and implementation of ELT pipelines using DBT and orchestrate workflows via Apache Airflow
  .
• Design, implement, and maintain robust data models to support analytics and reporting.
• Architect and optimize our cloud data warehouse in Snowflake
  , ensuring performance, scalability, and cost efficiency.
• Collaborate with data analysts and stakeholders to model and deliver well-documented, production-grade datasets.
• Establish data engineering best practices around version control, testing, CI/CD, and observability.
• Build and maintain data quality checks and data validation frameworks.
• Mentor junior data engineers and foster a strong engineering culture within the team.
• Collaborate on data governance efforts, including metadata management, data lineage, and access controls.
• Evaluate and integrate new tools and technologies to evolve our data stack.

• 8+ years of experience in data engineering with at least 2 years in a lead role.
• Strong experience designing and managing data pipelines with DBT and Airflow
  .
• Proven expertise in data modeling techniques (dimensional modeling, star/snowflake schemas, normalization, denormalization) and translating business requirements into scalable data models.
• Deep understanding of Snowflake
  , including performance tuning and cost optimization.
• Strong SQL and Python skills for data transformation and automation.
• Experience with Git-based workflows and CI/CD for data pipelines.
• Excellent communication skills and experience working with cross-functional teams.
• Experience with data cataloging and lineage tools
• Exposure to event-driven architectures and real-time data processing.
• Understanding of data privacy and security standards

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field