Senior Analytics Engineer

About the role

Redwood Materials is focused on creating a sustainable battery supply chain through the recovery, reuse, and recycling of battery materials. As part of our data and analytics team, you will engage in hands-on engineering tasks, primarily involving the development and maintenance of data pipelines that support various business functions. This role emphasizes coding and automated data analysis over traditional business intelligence tools. You will be responsible for designing the architecture of data movement and transformation processes that directly impact financial and operational decision-making. A significant portion of your work will involve writing efficient, scalable code to turn raw information into reliable inputs for business strategy. You will act as a technical partner to stakeholders, helping them understand the capabilities and limitations of data infrastructure. Success in this position requires a proactive approach to identifying data quality issues and implementing durable solutions. Ultimately, your work will ensure that the organization has a trusted, automated foundation for its most critical metrics.

Key facts

What you'll do

• Design and implement automated data pipelines for production using Python and SQL, ensuring they meet stringent reliability standards.
• Conduct in-depth one-time and automated analyses driven by financial and supply chain data to uncover actionable insights.
• Define technical solutions for data pipelines based on active discussions with stakeholders and a clear understanding of business objectives.
• Create and manage complex data workflows using orchestration tools like Dagster or Airflow, handling transformations with dbt.
• Employ robust CI/CD practices and adhere to solid software engineering principles, including version control, testing, and code reviews, in all data processes.
• Deploy and oversee pipelines within cloud environments, ensuring the high reliability and performance of delivered solutions.
• Collaborate closely with finance, supply chain, and operations teams to provide essential metrics, datasets, and automated processes that support their workflows.
• Take full ownership of projects from initial scoping through deployment, including prioritization, execution, and post-launch monitoring.
• Translate ambiguous stakeholder discussions into concrete technical data pipeline solutions that address root causes rather than symptoms.
• Develop monitoring and alerting strategies for data pipelines to proactively identify failures or performance degradations.
• Optimize query performance and data structures to handle increasing volumes of information efficiently.
• Document data architecture decisions and processes to ensure clarity and maintainability for current and future team members.
• Partner with data scientists and analysts to ensure that the data layer supports advanced modeling and reporting needs.
• Continuously evaluate new tools and methodologies to improve the efficiency and effectiveness of the analytics engineering function.

Requirements

• Possess a minimum of 3 years of professional experience in building, deploying, and maintaining production-grade data pipelines.
• Hold a bachelor's degree in a quantitative or technical discipline such as Data Engineering, Computer Science, or Applied Mathematics; a graduate degree is preferred.
• Demonstrate expertise in financial metrics or supply chain and operations domain knowledge, as this is essential for the role.
• Show proficiency in Python and SQL, with the ability to write complex queries and programmatic logic.
• Have hands-on familiarity with orchestration tools such as Dagster or Airflow, and substantial experience with dbt for transformation workflows.
• Maintain a basic understanding of cloud infrastructure concepts, including compute, storage, and networking services.
• Exhibit knowledge of CI/CD practices and sound software engineering methodologies, including testing frameworks and version control.
• Possess the ability to translate high-level stakeholder discussions into detailed technical data pipeline solutions.
• Display strong problem-solving skills and the capacity to debug intricate data flow issues under tight deadlines.
• Communicate effectively with both technical and non-technical team members to ensure alignment on project goals.
• Understand the importance of data governance and compliance in the context of sensitive business information.
• Be comfortable working in an agile environment where priorities can shift based on business needs.
• Demonstrate a commitment to writing clean, maintainable code that adheres to best practices.
• Show evidence of experience working with large datasets and optimizing processes for speed and reliability.

Nice to have

• Bring experience with AWS to the role, as it is a plus for managing cloud resources and services.
• Show knowledge across both financial metrics and supply chain/operations, which is beneficial for cross-functional collaboration.
• Include project management experience in your background, which is advantageous for coordinating timelines and deliverables.
• Have familiarity with Starburst and OpenMetadata, which is desirable for managing metadata and querying data ecosystems.

Practical notes

The position is full-time. Compensation will be based on experience.