Design, develop, and maintain robust, scalable, and efficient data pipelines to support business intelligence and AI/ML workloads.
Build and manage ETL/ELT processes to integrate data from diverse sources into centralized data platforms.
Ensure pipeline reliability, performance, and scalability through monitoring, troubleshooting, and continuous optimization.
Manage and maintain data infrastructure on AWS and Azure cloud platforms.
Develop and enforce data quality standards, validation processes, and governance best practices.
Partner with internal stakeholders across departments to understand reporting and analytics needs and translate them into scalable data solutions.
Enable and support BI tools (e.g, Tableau) by providing curated data models and optimized access layers.
Collaborate with data science and analytics stakeholders to ensure high-quality, well-structured data is available for model training and evaluation.
Provide technical guidance and mentorship to junior data engineers and analysts.

Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field preferred; or 6+ years of experience in data engineering or a related discipline in lieu of a degree.
Proficiency in SQL with strong experience in data modeling and query optimization.
Hands-on experience with Snowflake data platform.
Experience enabling BI tools through the design and delivery of secure, reliable data pipelines, curated data models, and performant data access layers.
Strong experience building and managing data pipelines and ETL/ELT workflows.
Proficiency with AWS/Azure cloud services.
Experience with Salesforce platform integrations or workflows.
Demonstrated ability to work collaboratively with both technical and non-technical stakeholders.

Senior Data Engineer

Key skills