10+ years experience, with 3+ years in a technical leadership role.

Lead the design and implementation of scalable data pipelines for ingesting, transforming, and activating customer data.

Develop and orchestrate workflows using Apache Airflow and Spark.

Leverage AWS services (e.G., S3, Glue, Athena, Redshift, EMR) to manage and optimize large-scale data infrastructure.

Write robust, modular, and testable code in Python to support data engineering use cases.

Experience developing or supporting AI-powered solutions is a strong plus.

Expert-level skills in SQL for data modeling, transformation, and analysis.

Hands-on experience with Snowflake, Redshift, and traditional data warehousing principles (star/snowflake schema, performance tuning, etc.)

Familiarity with real-time data streaming (Kafka) and event-based architectures.

Implement and manage CI/CD pipelines for data applications and infrastructure.

Exposure to CDPs (Customer Data Platforms) or Marketing Tech Platforms is a plus

Strong sense of urgency and ability to drive change.

Experience in agile methodologies (Scrum/Kanban/SAFE) and project management discipline.

Strong interpersonal and communication (written and verbal) skills.

Bachelors degree in computer science or related field.

Experience in Retail is a plus.

Data Pipeline Architect