Data Engineer-Python

Location: Cincinnati OH (Remote)

Job Overview: We are seeking an experienced Lead Software Engineer to join our Enterprise Data Platform Engineering team. The ideal candidate will have extensive experience designing, developing, and supporting scalable enterprise-grade software solutions, with strong hands-on expertise in Python development. The team is responsible for building and operating enterprise data platform capabilities that empower data engineers, data scientists, and application teams to develop, integrate, and deliver reliable data products efficiently. As a Lead Software Engineer, you will play a key role in designing and developing scalable backend services, APIs, and data-intensive applications. You will work across the enterprise data ecosystem, contributing to data ingestion, transformation, integration, data quality, observability, and platform engineering initiatives. This role requires a strong individual contributor who can independently write high-quality Python code, develop REST APIs, troubleshoot complex technical challenges, and lead engineering best practices while mentoring other developers.

Key Responsibilities: Hands-on Python Development: Design, develop, and maintain scalable, production-grade applications and backend services using Python. Strong coding and problem-solving skills are essential. API Development: Build, enhance, and maintain RESTful APIs and microservices using Python frameworks such as FastAPI or Flask. Enterprise Data Platform Engineering: Develop and support scalable data platform services, enabling efficient data ingestion, processing, transformation, and integration. Cloud-Native Development: Design and implement cloud-based applications and services leveraging Microsoft Azure technologies, including Azure Functions, Service Bus, and Azure Kubernetes Service (AKS).Data Engineering: Develop data-intensive applications using Databricks, PySpark, and SQL to support enterprise data processing requirements. Architecture and Design: Apply Domain-Driven Design (DDD), event-driven architecture, microservices principles, and object-oriented design patterns to build scalable and maintainable solutions. Engineering Excellence: Establish coding standards, implement automated testing, conduct code reviews, and ensure high-quality, maintainable, and reusable code. Performance Optimization: Troubleshoot production issues, perform performance tuning, optimize application workloads, and manage dependencies in complex production environments. CI/CD and DevOps: Contribute to automated build, deployment, testing, and release pipelines while promoting engineering best practices. Technical Leadership: Lead technical discussions, drive solution design, provide technical guidance, and mentor junior and mid-level engineers. Cross-Functional Collaboration: Work closely with product managers, architects, data engineers, and other engineering teams to translate business requirements into technical solutions. Continuous Improvement: Identify opportunities to improve platform scalability, reliability, automation, developer productivity, and operational efficiency. Future-Ready Platforms: Contribute to building AI-ready data platforms, intelligent observability capabilities, and automation-driven engineering solutions. Required Qualifications, Skills & Experience 10+ years of professional software development experience, including designing, developing, and maintaining enterprise-grade production applications. Strong hands-on Python development experience is mandatory. Candidates must have extensive experience writing production-quality Python code and developing backend applications. Strong proficiency in Python programming, including object-oriented programming, data structures, design patterns, exception handling, and dependency management. Hands-on experience developing RESTful APIs and microservices using FastAPI, Flask, or similar Python frameworks. Strong SQL skills and experience working with relational databases and structured data. Experience working with Microsoft Azure services, particularly Azure Functions, Service Bus, AKS, and other cloud-native services. Hands-on experience with Databricks and PySpark for large-scale data processing and data engineering workloads. Strong understanding of microservices architecture, Domain-Driven Design (DDD), and event-driven architecture. Experience with automated testing frameworks such as Pytest and Unittest, including unit, integration, and functional testing. Strong understanding of Git-based version control, branching strategies, and collaborative development practices. Experience with CI/CD pipelines, automated deployments, and DevOps practices. Strong understanding of SOLID principles, object-oriented design, clean coding practices, and software engineering fundamentals. Experience troubleshooting, debugging, and optimizing applications running in production environments. Familiarity with Agile development methodologies such as Scrum and XP.Ability to lead technical design discussions, mentor developers, and drive engineering best practices.

Preferred Qualifications: Experience with platform engineering, enterprise data platforms, and self-service data tooling. Exposure to front-end technologies such as Angular, React, and TypeScript. Experience building data quality, data observability, and monitoring solutions. Exposure to AI/ML platforms, AI-ready data architectures, and agentic automation frameworks. Experience designing highly available, scalable, and distributed cloud-native systems.

Preferred Certifications: Databricks Certified Data Engineer Professional. Microsoft Azure certifications, such as Azure Solutions Architect Expert or Azure Developer Associate.