Senior Data Engineer

Core Specialty Insurance Services•Cincinnati, OH

8d•Hybrid

About The Position

We are looking for a Senior Data Engineer to play a key senior technical role on our Data Engineering team, helping optimize and scale our existing large-scale data platform. This is a hands-on engineering role with a strong technical leadership component. You will design and build data pipelines and platform improvements while setting a strong technical example, reviewing the work of other engineers, and serving as a go-to resource for complex architecture and data engineering challenges. Reporting directly to the Director, Data Engineering, you will work alongside a small, focused team to build reliable, scalable data products and maintain a high-performing platform that supports evolving analytics and AI/ML needs. This role is well suited to an experienced data engineer seeking significant hands-on ownership, along with opportunities to mentor others and influence technical practices across the team.

Requirements

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over work authorization sponsorship now or in the future for this position.
Bachelor's degree in related field or demonstrated equivalent experience in a related field required.
7+ years of experience in data engineering, with experience working on large-scale, mature data platforms.
Demonstrated experience taking technical ownership of complex projects from design through delivery.
Experience contributing to data platforms that support downstream AI/ML use cases (e.g., feature stores, curated/governed datasets, streaming access for model training and inference).
Experience with IAC and CI/CD practices for data systems (i.e. Terraform, GitHub Actions)
Strong experience writing code modular code with notebooks
Deep expertise in data pipeline design, optimization, and distributed data processing architectures with experience identifying and resolving performance and scalability bottlenecks
Strong knowledge of cloud data platforms (AWS, Azure, or GCP) and modern data warehouse/Lakehouse architectures (Delta Lake, Iceberg)
Strong working proficiency with at least two programming languages (Python, Scala, SQL)
Solid understanding of data governance, security, and compliance practices in a regulated or enterprise environment
Ability to troubleshoot and reverse engineer existing codebases and data pipeline
Working knowledge of how data platforms enable AI/ML solutions

Nice To Haves

Experience mentoring or informally guiding other engineers, even without formal people management responsibility.
Experience optimizing the developer experience
Experience designing or implementing Agentic workflows for data engineering preferred
Experience working with Property & Casualty insurance carriers preferred
Experience with Data Vault 2.0 or Ensemble data modeling techniques preferred

Responsibilities

Design, build, and optimize data pipelines, ingestion frameworks, and platform components that support analytics, reporting, and downstream AI/ML use cases.
Take direct ownership of high-complexity or high-risk engineering initiatives, from technical design through implementation and rollout.
Identify and resolve performance, scalability, and reliability bottlenecks across the existing data platform.
Contribute to the platform's AI/ML readiness by improving data models, governance, and access patterns (e.g., feature stores, curated datasets, streaming access).
Diagnose and resolve complex production issues, including on-call support for critical data pipeline failures.
Write clean, well-tested, well-documented code and infrastructure-as-code, and maintain strong engineering hygiene across your work.
Act as a senior technical resource for the team, providing guidance on architecture, design patterns, and best practices.
Conduct code and design reviews, helping raise the technical bar across the Data Engineering team.
Partner closely with the Director, Data Engineering on technical design decisions, tooling evaluations, and platform roadmap input.
Mentor other data engineers, sharing knowledge and helping develop their technical skills.
Partner cross-functionally with Product and Engineering stakeholders to understand data needs and translate them into technical solutions.
Help document standards, runbooks, and architectural decisions to support team scalability and knowledge sharing.
Other duties as assigned.