Lead Data Engineer

ROLES AND RESPONSIBILITIES

Design and maintain data architecture using Snowflake, Azure, and Python for robust data

solutions.

Develop and optimize ELT/ETL workflows with Python, SQL, and Spark for data accuracy

and scalability.

Development and deployment of data-driven solutions, supporting Gen AI and AI

applications.

Apply software engineering principles to build scalable, maintainable data and application

solutions.

Collaborate with cross-functional teams to define business requirements and architect data

solutions.

Ensure compliance with data privacy regulations and best practices.

Implement DevOps processes to automate deployment and testing of data pipelines and

software.

Stay current on data engineering, Gen AI, and marketing technology trends, recommending

adoption.

Deliver high-quality, scalable solutions in an Agile environment, meeting deadlines and

budgets.

TECHNICAL COMPETENCIES (Knowledge, Skills & Abilities)

Expert in Snowflake pipelines for data workloads in Azure or AWS.

Strong data modeling skills for designing efficient, scalable database structures.

Knowledge of AI platforms.

Strong software engineering skills, including React, JavaScript, tools (Node.js, Git,

Webpack).

Advanced Python fluency for data engineering and SQL expertise for data optimization.

Excellent communication skills.

Self-motivated, results-oriented, data excellence-focused.

EDUCATION AND EXPERIENCE

Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or related

field; Master's degree preferred.

8+ years of experience in data engineering, with a focus on designing and building data

pipelines and architecture.

6+ years of hands-on experience with Snowflake, Azure, and Python in data solutions.

Proven track record in software engineering, with experience in React and modern

development tools.

Demonstrated leadership in delivering scalable, data-driven solutions in an Agile

environment.