Big Data Engineer III (60641)

This is a remote role that begins with an in-person onboarding experience at our corporate office in Providence, RI to establish strong connections and set the foundation for success. During this time, new team members will learn our systems and processes while building relationships with colleagues. We also expect team members to be onsite a few times per year for team building and key project kickoffs. Travel expenses are fully covered by AAA Northeast.

At AAA Northeast, how we work together matters. We are a highly collaborative organization that values connection, transparency, and trust. Our “cameras on” approach during virtual meetings reflects our expectation that team members are present, engaged, and actively participating, helping to build strong working relationships and a sense of shared accountability, no matter where we’re located.

Big Data Engineer III is responsible for designing, developing, and maintaining large-scale data processing systems. This role includes building and optimizing data pipelines and ETL processes, designing and maintaining data models and architectures, and conducting performance tuning and optimization of data processing systems. Collaboration with data scientists and analysts is essential to deliver actionable insights.

What you will do:

• Data Engineering: Architect and optimize ETL processes for complex data requirements. Design advanced data models to support sophisticated data processing needs. Design and manage robust, scalable data pipelines.
• Database Management: Oversee the management and optimization of databases. Utilize advanced SQL techniques for complex data operations. Oversee the implementation and management of NoSQL databases. Architect and manage data warehousing solutions.
• Big Data and Cloud Technologies: Lead the implementation and optimization of big data technologies. Manage and optimize distributed computing resources for large-scale data processing. Build, maintain, and manage data pipelines using cloud technologies, Snowflake, Fivetran, DBT, Airflow. Utilize cloud platforms for scalable data processing and storage.
• DevOps and Security: Apply DevOps practices to automate and streamline data engineering workflows. Implement containerization solutions for data processing jobs. Implement data security measures to protect sensitive information. Optimize the performance of data processing and storage systems.
• Leadership: Mentor and guide junior engineers, fostering a collaborative and innovative work environment.