Job descriptionJOB OVERVIEW As a Senior Data Engineer, you will play a critical role in helping the organization leverage data and technology to drive business growth, customer engagement, and data-driven decision-making. The primary responsibilities will be building, managing, and optimizing data pipelines as well as AI tools effectively into production for critical data and analytics consumers like business/data analysts, data scientists, or any persona needing curated data for data and analytics use cases across the enterprise.
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. 8-10 years of experience in data engineering, with a focus on designing and building data pipelines and architecture. 8-10 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.