Data Engineer Team Lead

We are seeking a high-caliber Data Engineer Team Lead to spearhead the evolution of our data infrastructure. We operate at the intersection of AI-driven optimization and retail inventory management, handling massive streams of real-time data to help global brands make smarter decisions.

In this role, you will balance technical leadership with hands-on engineering. You will be responsible for designing scalable data pipelines, overseeing our data architecture, and mentoring a talented team of engineers to ensure our data is reliable, accessible, and high-performing.

Core Responsibilities

• Team Leadership: Lead, mentor, and grow a team of data engineers. Conduct code reviews, facilitate technical discussions, and foster a culture of engineering excellence.
• Architecture & Design: Design and implement robust, scalable, and automated data pipelines (ETL/ELT) that support real-time and batch processing.
• Data Governance: Ensure the highest standards of data quality, integrity, and security across all environments.
• Cross-Functional Collaboration: Partner with Data Scientists, Product Managers, and Backend Engineers to translate business requirements into technical data solutions.
• Innovation: Stay at the forefront of data engineering trends. Evaluate and implement new technologies to improve our data stack's efficiency and cost-effectiveness.
• Hands-on Development: Writing clean, maintainable, and efficient code to solve complex data challenges.
  
  

• Experience: 5+ years in Data Engineering, with at least 1-2 years in a leadership or "lead" capacity.
• Data Stack Proficiency: Deep experience with cloud data warehouses (e.g., Snowflake, BigQuery) and orchestration tools (e.g., Airflow, Dagster).
• Programming: Mastery of Python and advanced SQL.
• Big Data Tech: Experience with Spark, Kafka, or similar distributed processing frameworks.
• Cloud Infrastructure: Proven experience working within AWS, GCP, or Azure environments.
• Modeling: Strong understanding of data modeling (Star Schema, Data Vault) and modern tools like dbt.
  
  

• Experience in the Retail, Supply Chain, or Fintech sectors.
• Background in building data products that support machine learning models at scale.
• Familiarity with IaC (Infrastructure as Code) tools like Terraform.
• Experience working in a fast-paced, high-growth startup environment.