About the role

Data Engineer developing scalable data pipelines for RunBuggy's automotive logistics platform. Collaborate with cross-functional teams to unlock powerful insights and optimize data infrastructure.

Responsibilities

Design, develop, and maintain scalable data pipelines and systems.
Independently create and own new data capture/ETL’s for the entire stack and ensure data quality.
Collaborate with data scientists, engineers, business leaders, and other stakeholders to understand data requirements and provide the necessary infrastructure.
Create and contribute to frameworks that improve the effectiveness of logging data, triage issues, and resolution.
Define and manage Service Level Agreements (SLA) for all data sets in allocated areas of ownership.
Lead data engineering projects and determine the appropriate tools and libraries for each task.
Implement data security and privacy best practices.
Create and maintain technical documentation for data engineering processes.
Work with cloud-based data storage and processing solutions (for example, Docker and Kubernetes).
Build out and support a DAG orchestration cluster framework.
Migrate workflows from batch processes to the DAG cluster via concurrent data flows.
Data pipeline maintenance, including debugging code, monitoring, and incident response.
Collaborate with engineering to enforce data collection and data contracts for API’s, databases, etc.
Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts.

Bachelor's degree in Computer Science, Engineering, or a related field required; master’s degree preferred.
5+ years of experience in data engineering.
Proficiency in Python and experience with data engineering libraries (e.g., Pandas).
Experience with ETL processes and tools.
Strong knowledge of relational and non-relational databases.
Experience with cloud platforms (e.g., AWS, GCP, Azure).
Excellent communication skills.
Ability to work independently and lead projects.
Experience with data warehousing solutions.
Familiarity with data visualization tools (e.g., Tableau).
Experience with building and managing DAG clusters (e.g. Airflow, Prefect).
Ability to work with the following: JavaScript, Node.js, AngularJS, Java, and Java Spring Boot.
Knowledge of machine learning and data science workflows.
Ability to handle a variety of duties in a fast-paced environment.
Excellent organizational skills, along with professionalism and diplomacy with internal and external customers/vendors.
Ability to prioritize tasks and manage time.
Ability to work under tight deadlines.

Highly competitive medical, dental, vision, Life w/ AD&D, Short-Term Disability insurance, Long-Term Disability insurance, pet insurance, identity theft protection, and a 401(k) retirement savings plan.
Employee wellness program.
Employee rewards, discounts, and recognition programs.
Generous company-paid holidays (12 per year), vacation, and sick time.
Paid paternity/maternity leave.
Monthly connectivity/home office stipend if working from home 5 days a week.
A supportive and positive space for you to grow and expand your career.