Описание

Oportun is hiring a Senior Data Analytics Engineer to design, build, and maintain scalable data architectures, ETL pipelines, warehouses, and lakes. The role includes data quality, governance, observability, mentoring, and leading cross-functional data initiatives.

Responsibilities

Design and implement scalable, efficient, and reliable data architectures that support business and analytical needs
Build and maintain data pipelines, ETL processes, and integration solutions for large volumes of structured and unstructured data
Optimize data pipelines, databases, data warehouses, and data lakes for performance, reliability, scalability, and security
Partner with stakeholders to understand data requirements, develop domain expertise, and translate business needs into effective data models and solutions
Establish and improve data quality standards, validation rules, documentation, and governance practices
Implement monitoring and observability practices to identify bottlenecks, improve performance, and strengthen platform reliability
Provide technical leadership on architecture, scalability, reliability, monitoring, integration, and extensibility
Lead and contribute to code reviews, helping maintain high standards for code quality, performance, and maintainability
Mentor junior engineers and support a culture of continuous learning and technical excellence
Take ownership of production issues, including troubleshooting, root-cause analysis, escalation, and long-term resolution
Independently lead multiple features and projects, coordinate work across engineers, and keep stakeholders informed of progress, risks, and dependencies
Help evolve engineering tools, platforms, and practices and encourage adoption of better ways of working
Look for practical ways to use AI tools to improve engineering productivity, analysis, documentation, and problem-solving

Requirements

8+ years of experience in data engineering, with strong experience in data architecture, ETL, and database management
Strong programming skills in Python or PySpark, plus experience with Java or Scala
Experience building complex end-to-end data pipelines and data integration solutions
Strong knowledge of SQL and experience with relational and NoSQL database technologies
Experience with big data technologies such as Spark, Kafka, Hadoop, or similar platforms
Experience with orchestration and scheduling tools such as Airflow, Databricks, Jenkins, or similar technologies
Experience designing and operating scalable, reliable, and secure data systems
Familiarity with cloud platforms such as AWS, Azure, or GCP and associated data services
Experience working in Agile environments such as Scrum, Lean, or Kanban
Strong problem-solving and decision-making skills
Experience mentoring junior engineers and contributing to technical leadership within a team
Strong written and verbal communication skills with the ability to work effectively across technical and non-technical teams

Nice to have

Bachelor

The right fit looks like this You're a hands-on data engineer who enjoys solving complex technical problems and building systems that others depend on. You combine strong technical depth with a practical understanding of business needs and know how to turn ambiguous requirements into scalable solutions. You take ownership, communicate clearly, and are comfortable leading technical work without relying on formal authority. You enjoy mentoring others and helping teams make stronger technical decisions.