Tech Lead Data Engineer

Circle K•Tempe, AZ

30d

About The Position

As the Tech Lead Data Engineer , your primary responsibility will be to lead the design, development, and implementation of data solutions while driving strategic initiatives across the enterprise. This role requires you to guide a team of data engineers, facilitate cross-functional collaboration, and act as a subject matter expert to ensure seamless integration between business objectives and technical implementations.

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Proven experience (8+ years) in a data engineering role, with expertise in designing and building ETL pipelines, data models, and warehouses.
Strong proficiency in Azure, Snowflake, Databricks, SQL, Python, and Spark.
Strong experience with cloud platforms such as AWS, Azure, or GCP is a must.
Experience working with Apache Iceberg and distributed computing frameworks.
Strong communication skills & demonstrated leadership ability to manage relationships across cross-functional teams and global stakeholders.
Hands-on experience with CI/CD tools and DevOps practices for automation.
Retail industry experience with familiarity in processing transaction data, inventory data, and customer insights.
Applying data modeling concepts, data warehousing architectures, and data management best practices.

Responsibilities

Provide day-to-day technical leadership for key company initiatives
Lead design and development efforts for scalable data pipelines and solutions leveraging Azure, Databricks, Snowflake, and Apache Iceberg.
Collaborate with business teams, architects, business analysts, source system owners, and business stakeholders to ensure enterprise data requirements are met.
Guide and mentor data engineers to align with organizational standards and best practices.
Drive critical conversations across platform, business, and technical teams to ensure timely and efficient delivery of projects.
Lead data modeling efforts to design and optimize schemas, ensuring data integrity and performance.
Oversee the documentation of engineering processes to ensure knowledge retention and scalability.
Actively participate in architectural and strategic decisions while ensuring compliance with data governance, security, and privacy requirements.
Establish CI/CD pipelines and DevOps practices for automating deployment and ensuring operational excellence.
Act as the primary point of contact for cross-regional teams, facilitating knowledge transfer and resolving dependencies.