Director – Data Engineering

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and execute a scalable lakehouse medallion architecture within Databricks.

• Establish ingestion, canonical, and business-ready data modeling layers with defined standards and naming conventions.

• Create and sustain structured, governed fact and dimension models for enterprise reporting.

• Supervise ingestion pipelines utilizing Fivetran, Airbyte, and custom integrations while enhancing cost-effectiveness and performance.

• Develop and oversee SQL and Python transformation jobs, which include incremental processing, upsert logic, and snapshot modeling.

• Implement orchestration, monitoring, data quality validation, and failure recovery mechanisms.

• Define enterprise data governance standards encompassing access controls and reconciliation processes.

• Integrate ERP, Shopify, GA4, Google Ads, Meta Ads, and catalog marketing data into cohesive customer and order models.

• Lead and guide a small team of data and analytics engineers while establishing coding and review standards.

⛳️ Requirements

• Over 7 years of experience in data engineering, analytics engineering, or data architecture.

• More than 3 years of experience leading data platform or warehouse initiatives.

• Expert-level knowledge in Databricks and medallion architecture design.

• Advanced proficiency in SQL and substantial experience in Python for data transformations.

• Experience in designing fact/dimension models and implementing incremental pipelines and snapshot logic.

• Strong grasp of data governance, access control, and quality frameworks.

• Experience integrating commerce, finance, ERP, and marketing data sources into structured models.

• Excellent communication skills with the capability to collaborate across technical and business teams.

🏝️ Benefits

• Valued Contribution: Build the foundational data infrastructure that powers enterprise decisions.

• Growth Opportunities: Shape standards, architecture, and long-term data strategy.

• Team Environment: Partner with business leaders and analytics teams to deliver trusted insights.

• Purpose Driven Work: Enable scalable analytics that strengthen operations, finance, and commerce performance.