Qualifications

• 5-7 years of experience in data engineering roles.
• Strong hands-on experience with Databricks, PySpark, and Spark SQL.
• Proven experience implementing Medallion architecture.
• Solid data modeling skills for analytics and reporting.
• Experience leading small engineering teams without formal management responsibility.
• Demonstrated ability to collaboratively refine unclear requirements.
• Excellent written and verbal communication skills, especially in remote settings.

Responsibilities

• Lead a small delivery team while managing complex data transformations and modeling.
• Keep work unblocked and well-scoped to ensure consistent delivery.
• Build and refine analytics foundations using Gold-layer data models.
• Design and implement Medallion architecture transformations.
• Ensure performance and consistency of Gold-layer outputs for analytics engines.
• Enhance reliability and maintainability of existing data pipelines.
• Collaborate with the Engineering Manager on executing the Data Warehouse Unification Plan.
• Prepare and deliver sprint-based execution with a focus on completion.
• Identify and surface execution risks and dependencies early.
• Translate specifications into clear, actionable work tickets.
• Assign tasks intelligently based on team members' skills.
• Directly implement complex Spark and Databricks transformations as needed.
• Review pull requests to maintain quality standards.
• Proactively communicate progress and any blockers to stakeholders.
• Maintain momentum with minimal process overhead.

Benefits

• Flexible work environment with remote options.
• Opportunity to lead a small team and influence data strategy.
• Access to cutting-edge tools and technologies in data engineering.
• Collaborative team culture that encourages knowledge sharing.
• Focus on personal and professional growth through hands-on experience.