Data Engineerš Location: Columbus, Ohio, United States (Hybrid)š¢ Industry: Hospitals and Health Careš¼ Work Setting: HybridAre you passionate about building scalable data platforms, engineering reliable data pipelines, and transforming complex data into meaningful business insights?
We are seeking a skilled Data Engineer who thrives in a fast-paced environment and enjoys designing, developing, and supporting modern data solutions that power analytics, reporting, and critical business operations.
In this role, you will be responsible for developing scalable data pipelines, integrating diverse data sources, and ensuring high-quality, trusted data assets across the organization. You will collaborate with cross-functional teams to deliver innovative data solutions while contributing to best practices in data engineering, governance, and platform optimization.
Key Responsibilities
- Data Engineering & Pipeline Development
- Design, develop, and maintain scalable and efficient data pipelines to support reporting, analytics, and operational requirements.
- Build and manage data ingestion and integration processes across multiple structured and unstructured data sources.
- Develop and optimize data transformation workflows using modern cloud-based data technologies and SQL-based processing frameworks.
- Support both batch and real-time data processing architectures to meet evolving business needs.
- Implement data quality, validation, monitoring, and reconciliation processes to ensure reliable and trusted datasets.
- Troubleshoot and resolve data pipeline performance, scalability, reliability, and quality-related issues.
- Continuously improve data platform performance through optimization and automation initiatives.
- Data Modeling & Business Collaboration
- Design and maintain conceptual, logical, and physical data models aligned with business and reporting requirements.
- Collaborate with business stakeholders, analysts, and technical teams to gather requirements and translate them into scalable data solutions.
- Work closely with application and platform teams to understand source systems and develop efficient data integration frameworks.
- Support enterprise data governance initiatives through documentation, standardization, metadata management, and quality controls.
- Enable self-service analytics by providing well-structured, accessible, and trustworthy data assets.
- Collaboration & Technical Leadership
- Partner with analytics, reporting, and technology teams to solve complex business challenges using data.
- Communicate technical concepts and solution designs effectively to both technical and non-technical stakeholders.
- Leverage modern engineering practices, automation tools, and emerging technologies to improve development efficiency and solution quality.
- Contribute to knowledge sharing initiatives and provide guidance to junior team members.
- Participate in code reviews, technical discussions, and continuous improvement activities to strengthen team capabilities.
Required Qualifications
- Bachelorās degree in Computer Science, Information Technology, Information Systems, Engineering, or a related discipline, or equivalent professional experience.
- Minimum of 4 years of experience in a dedicated Data Engineering role.
- Proven experience building, maintaining, and supporting enterprise-scale data pipelines and integration solutions.
- Strong hands-on expertise with modern cloud-based data platforms and distributed data processing environments.
- Advanced SQL development, optimization, and troubleshooting skills.
- Experience working with cloud-native data services and modern analytical ecosystems.
- Knowledge of data warehousing, ETL/ELT development, and data integration best practices.
- Strong understanding of structured and unstructured data processing.
- Experience supporting reporting, analytics, data governance, and business intelligence initiatives.
- Expertise in conceptual and logical data modeling techniques.
- Strong problem-solving, analytical, and debugging capabilities.
- Excellent written, verbal, and interpersonal communication skills.
Preferred Qualifications
- Experience with real-time data streaming and event-driven architectures.
- Familiarity with infrastructure automation and Infrastructure-as-Code practices.
- Experience supporting large-scale cloud modernization, migration, or transformation initiatives.
- Exposure to AI-assisted development tools and modern software engineering practices.
- Experience working with highly available, business-critical data platforms.
- Proven ability to mentor junior engineers and provide technical leadership within collaborative teams.
- Understanding of enterprise data governance, metadata management, data lineage, and data quality frameworks.
- What Success Looks Like
- Delivering scalable, reliable, and high-performing data solutions that support business growth and decision-making.
- Ensuring data quality, integrity, security, and governance standards are consistently maintained.
- Building trusted data assets that empower reporting, analytics, and operational processes.
- Driving innovation through modern cloud technologies, automation, and engineering best practices.
- Collaborating effectively across teams to translate business needs into impactful data solutions.
- Contributing to a culture of continuous learning, knowledge sharing, and technical excellence.
