Data Engineer

Position Summary

As a Senior Data Engineer at Assent, you will play a critical role in advancing our data engineering practices and serving as a hands-on technical expert. You will contribute significantly to the vision and execution of our data engineering efforts, ensuring the development of secure, robust, scalable, and high-performing data platforms. Your role will involve driving key technical initiatives, collaborating on architectural decisions, and executing complex data engineering tasks to align our data infrastructure with Assent's business goals.

You will actively participate in the design, development, and implementation of sophisticated data solutions while offering mentorship and technical guidance to other engineers. Your contributions will have a broad impact across the organization as you champion best practices, innovate to enhance our data engineering capabilities, and work directly on the technical solutions required to advance our data systems.

Key Requirements & Responsibilities

• Contribute to the strategic vision for data engineering and participate in the architectural design and development of new and complex data solutions, focusing on scalability, performance, and hands-on implementation.
• Design and implement new data systems and infrastructure to ensure the reliability and scalability of data systems by actively contributing to day-to-day engineering tasks.
• Influence key decisions regarding the data technology stack, infrastructure, and tools while actively engaging in hands-on engineering efforts in the creation and deployment of new data architectures and workflows.
• Set coding standards and best practices for the Data Engineering & Operations team, conducting and participating in code reviews to maintain high-quality, consistent code.
• Work closely with database developers, software development, product management, and AI/ML developers to align data initiatives with Assent’s organizational goals.
• Collaborate with team members to monitor progress, adjust priorities, and meet project deadlines and objectives.
• Identify opportunities for internal process improvements, including automating manual processes and optimizing data delivery.
• Proactively support peers in continuous learning by providing technical guidance and training on data engineering development, analysis, and execution.