Data Team Lead

Edikted is one of the fastest-growing global e-commerce powerhouses. We’ve disrupted the fashion industry by combining real-time data analytics with rapid-response supply chains, achieving remarkable revenue growth and a strong market presence in record time. With a high-tech mindset, we leverage advanced consumer insights to stay ahead of trends.

If you want to work in an environment where the speed of business matches the speed of data, this is the place for you.

We are looking for a Data Team Lead to scale and guide our data engineering team, own our data platform end-to-end, and collaborate with cross-functional teams to drive innovation and business growth. This role blends leadership with hands-on technical work—ideal for someone who enjoys managing people while remaining deeply involved in engineering execution.

Responsibilities:

• Lead and mentor the data engineering team, setting goals, providing guidance, and fostering growth.
• Design and maintain scalable data architecture across ingestion, warehousing, modeling, and governance.
• Collaborate with Product, Analytics, and Engineering teams to deliver data solutions that power key business decisions.
• Partner with the VP Analytics to shape and optimize our BI and analytics infrastructure.
• Stay hands-on: build and review pipelines, ensure data quality, and improve system performance.
• Establish and uphold best practices in testing, CI/CD, documentation, and data governance.
• Define team roadmaps, set priorities, and communicate effectively with all stakeholders.

Requirements:

• 6+ years of experience in data engineering, including at least 2 years in a leadership or team lead role.
• Proven experience designing and maintaining modern cloud-based data architectures (batch and streaming).
• Strong SQL and Python skills with deep understanding of data modeling and transformation frameworks.
• Hands-on experience with orchestration tools (e.g., Airflow, Prefect) and dbt.
• Experience working with major data warehouses (BigQuery, Snowflake, Redshift, or Databricks).
• Familiarity with data quality and observability tools (e.g., dbt tests, Great Expectations, Soda).
• Excellent communication and leadership skills, with the ability to drive both strategy and execution.

Nice to Have:

• Experience in eCommerce or consumer data environments.
• Knowledge of event streaming and customer data tools (Kafka, Segment, GA4).
• Exposure to experimentation platforms or ML feature stores.
• Understanding of data privacy and governance (GDPR, RBAC, data retention).