Senior Data Engineer

Job Location CINCINNATI GENERAL OFFICES Job Description As a Senior Data Engineer, you will be a technical leader and expert, responsible for architecting, designing, and implementing highly scalable and robust cloud-based data and analytics platforms (DAP) and complex data pipelines. You will drive the strategy for acquiring, cleansing, transforming, and publishing critical data assets from diverse enterprise and external sources. Beyond building cutting-edge data solutions, you will act as a principal liaison, partnering deeply with senior business stakeholders, solution architects, and analytics leaders to define technical roadmaps, significantly influence data architecture, and establish enterprise-wide engineering standards and best practices. We seek individuals who are not only masters of current technologies but are also visionary, continuously exploring and integrating emerging data engineering paradigms and tools to push the boundaries of what's possible.

Strategic Technical Leadership: Lead the architectural design and implementation of complex, large-scale data solutions, ensuring scalability, performance, security, and cost-efficiency. Partner with senior business stakeholders and product owners to deeply understand strategic business objectives and translate them into architectural blueprints and technical roadmaps for data platforms. Influence and drive the overall data strategy, architecture, and technology choices across multiple teams or domains. Advanced Data Platform & Pipeline Development: Architect, build, and optimize highly resilient, performant, and secure ETL/ELT pipelines on modern cloud data platforms, handling petabyte-scale data volumes and real-time processing requirements. Design and implement advanced data integration patterns, connecting complex enterprise systems, third-party services, streaming sources, and APIs, ensuring high data availability and reliability. Drive the adoption of advanced data processing techniques (e.g., stream processing, graph databases, data mesh principles). Mentorship & Community Building: Serve as a primary technical mentor and subject matter expert for a team of data engineers, providing guidance on complex technical challenges, architectural decisions, and career development. Lead code reviews, design discussions, and technical workshops, fostering a culture of excellence and continuous improvement. Champion and evolve our enterprise-wide engineering standards, best practices, and governance for data (e.g., data quality frameworks, testing automation, CI/CD pipelines, security protocols, documentation standards, data observability). End-to-End Ownership & Operational Excellence: Take ultimate end-to-end ownership for critical data solutions, from strategic inception and architectural design through implementation, deployment, advanced monitoring, performance tuning, and incident response for production systems. Implement robust data quality frameworks, observability solutions, and anomaly detection to ensure the highest integrity and reliability of data assets. Innovation & AI Integration: Proactively evaluate, prototype, and integrate cutting-edge technologies, including advanced Generative AI models and sophisticated agentic systems, to dramatically enhance developer productivity, automate complex tasks, and create novel data solutions. Act as a thought leader in the responsible and ethical application of AI in data engineering, ensuring best practices for security, privacy, and bias mitigation. Lead initiatives for continuous learning and knowledge sharing across the broader engineering organization. Modern Development Practices: Master modern development tools and practices, including advanced IDE features, sophisticated Git strategies (e.g., monorepos, gitflow), infrastructure as code (IaC), and advanced CI/CD pipelines tailored for data platforms. Job Qualifications Required:

Bachelor's or Master's degree in Computer