Job Title: Data Engineer
Location: Cincinnati, OH-Onsite role
Duration: 11 months contract
Job Description:
General Function:
The Data Engineer designs and builds data platforms, tools, and solutions that enable the bank to manage, secure, and extract value from its data. This role involves developing scalable, reusable solutions for collecting, storing, processing, and serving data across both traditional and modern architectures. Engineers work with technologies ranging from IBM DB2 and IBM Information Server (DataStage) to Snowflake and dbt, supporting both on-premise and cloud-based environments. The role also includes leveraging GenAI capabilities to boost productivity and prepare data for AI-readiness, while owning the full lifecycle of data assets to ensure quality, discoverability, and governance.
Responsible and accountable for risk by openly exchanging ideas and opinions, elevating concerns, and personally following policies and procedures as defined. Accountable for always doing the right thing for customers and colleagues while ensuring that actions and behaviors drive a positive customer experience. While operating within the Bank's risk appetite, achieves results by consistently identifying, assessing, managing, monitoring, and reporting risks of all types.
Essential Duties & Responsibilities:
- Responsible for design, development, and support of scalable data solutions, APIs, tools, and processes that enable rapid delivery of business capabilities across both traditional and modern data platforms.
- Work closely with IT application teams, Enterprise architecture, infrastructure, information security, and LOB stakeholders to translate business and technical strategies into data-driven solutions for the Bank.
- Act as a technical Expert addressing problems related to system and application design, performance, integration, security, etc.
- Conduct research and Development based on current trends and technologies related to the banking industry, data engineering and architecture, data security, AI-readiness, and related topics.
- Build and maintain CI/CD pipelines and self-service deployment tools to streamline development and operations.
- Evaluate data and software products, providing documented recommendations to improve capabilities.
- Provide support and troubleshooting for data pipelines and platforms, including escalated on-call support for critical incidents.
- Participate in planning and execution of internal projects, including but not limited to, legacy system modernizations, modernizing data pipelines, monitoring, and documentation improvements.
- Optimize and automate data pipelines for efficiency, scalability, observability, and performance.
- Leverage GenAI tools to enhance engineering productivity and support the preparation of data for AI and machine learning use cases.
- Apply a data product mindset by managing the full lifecycle of data assets, ensuring quality, discoverability, and governance.
- Mentor and provide technical guidance to other team members.
- Manage and prioritize multiple assignments in a dynamic environment.
- Foster collaboration and continuous learning through cross-functional initiatives, mentoring, and knowledge sharing.
- Deliver high-impact data solutions in Agile teams through close collaboration with product owners and stakeholders.
Joshua Gidugu
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