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About our team - Data Ventures
Data Ventures exists to unlock the full value of Walmart’s data by developing and productizing B2B data initiatives that empower merchants and suppliers to make better, faster decisions for the business. As part of this transformation, we’re seeking entrepreneurial individuals to help drive data productization from concept to deployment.

What You'll Do:

• Design, develop, and optimize highly scalable backend services and distributed systems using Java, Spring Boot, microservices, REST APIs, and event-driven architectures.

• Own complex technical solutions from design through implementation, testing, deployment, observability, and production support.

• Define and influence technical architecture across multiple services and teams, balancing scalability, reliability, performance, security, and maintainability.

• Build reusable components, frameworks, APIs, and engineering capabilities that improve developer productivity and accelerate product delivery.

• Design and implement event-driven solutions using technologies such as Apache Kafka, ensuring reliable and scalable communication across distributed services.

• Integrate backend applications with enterprise data platforms and support batch and streaming data processing use cases.

• Apply working knowledge of Apache Spark and distributed data processing concepts when developing or integrating data-intensive applications.

• Collaborate with Data Engineering, AI/ML, Platform, Infrastructure, and Product teams to deliver scalable solutions supporting operational, analytical, and AI/ML workloads.

• Drive engineering excellence through code reviews, architecture reviews, automated testing, CI/CD, observability, performance engineering, and operational best practices.

• Identify and resolve complex production issues through structured debugging, root cause analysis, and sustainable corrective actions.

• Mentor engineers through technical guidance, design discussions, code reviews, and knowledge sharing.

• Influence engineering standards, design patterns, and best practices across teams.

• Evaluate emerging technologies and drive adoption of solutions that improve scalability, reliability, developer productivity, and customer experience.

• Maintain architectural decision records and communicate technical decisions, trade-offs, and long-term implications to stakeholders.

• Partner with Product and business stakeholders to translate complex requirements into scalable and measurable technical solutions.

What You'll Bring:

• 10+ years of software engineering experience with significant experience building and operating large-scale backend applications.

• Strong hands-on expertise in Java and modern backend frameworks such as Spring Boot.

• Deep understanding of microservices, distributed systems, API design, and event-driven architectures.

• Strong experience with REST APIs, asynchronous processing, messaging systems, and SQL/NoSQL databases.

• Experience with Apache Kafka or similar distributed messaging and streaming technologies.

• Working knowledge of data engineering concepts, including ETL/ELT, batch and streaming processing, data pipelines, and data quality.

• Familiarity with Apache Spark or other distributed data processing frameworks; hands-on experience is a plus.

• Understanding of cloud-native development and experience with platforms such as Azure, AWS, or GCP.

• Experience with Docker, Kubernetes, CI/CD, and observability/monitoring.

• Strong understanding of software architecture, design patterns, performance optimization, resiliency, and fault-tolerant systems.

• Experience designing systems for high availability, scalability, and operational excellence.

• Strong problem-solving skills with the ability to simplify complex technical problems and make sound architectural decisions.

• Ability to influence technical direction across teams without relying on formal authority.

• Demonstrated ability to mentor engineers and raise engineering standards across the organization.

• Strong communication and collaboration skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.

• Passion for continuous learning, innovation, automation, and improving engineering productivity.

• Experience integrating AI/ML capabilities or GenAI tools into software solutions is a plus.