Data Engineer at Onepoint developing cloud - native architectures and scalable data solutions. Collaborating on data processing pipelines and guiding clients on best practices.
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.
Requirements
- 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.
Benefits
- 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.
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Data Engineer at Onepoint contributing to client growth through cloud technologies. Involves data pipeline development, auditing cloud configurations, and supporting data science practices.
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