Lead Data Engineer

About the Role:

Lead Data Engineer

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.

Key Responsibilities:

• Lead the design and implementation of ELT pipelines using

  DBT

  and orchestrate workflows via

  Apache Airflow

  .
• 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.

Requirements:

• 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

  .
• 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

Education:

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