Senior Data Integrations Engineer

The Senior Data Engineer is responsible for designing, building, and maintaining the systems and infrastructure that enable organizations to collect, store, process, and analyze large volumes of data. This role involves collaborating closely with data scientists, analysts, QA engineers, business process / functional SMEs, and other stakeholders to ensure that data is accessible, reliable, and secure. They are responsible for tasks such as data ingestion, data transformation, data integration, and data pipeline development. Senior Data Engineers also play a crucial part in data governance, ensuring that data is compliant with regulations and policies. This role also includes all aspects of software development and deployment of IT Operations to shorten delivery and time to market for data products and data pipelines and data warehousing. Overall, the incumbent helps organizations leverage their data to gain meaningful insights and make informed decisions.

This position is not hybrid/remote and will be located at our Cleveland Headquarters office.

This position is not eligible for sponsorship for work authorization now or in the future, including conversion to H1-B visa.

Job duties include contact with other employees and access confidential and proprietary information and/or other items of value, and such access may be supervised or unsupervised. The Company therefore has determined that a review of criminal history is necessary to protect the business and its operations and reputation and is necessary to protect the safety of the Company’s staff, employees, and business relationships.

• Partner with a team of data engineers, providing technical guidance, mentorship, and support
• Act as a technical point of contact for clients and stakeholders, providing updates and addressing any data related technical inquiries or concerns
• Design, develop, and maintain efficient and robust data pipelines, ETL processes, and data workflows
• Develop and maintain data models and schema designs to support data storage and retrieval needs
• Optimize data storage, processing, and retrieval mechanisms for performance and scalability
• Provide technical leadership and guidance in the selection and implementation of data engineering tools and technologies
• Identify and implement best practices and standards for data engineering processes and tools
• Stay up-to-date with emerging technologies and trends in data engineering, evaluating their potential impact on our data infrastructure
• Collaborate with cross-functional teams to integrate data sources and enable seamless data flow across systems and with data scientists, analysts, and stakeholders to understand data requirements and develop scalable data solutions
• Implement and maintain data governance and security measures to protect sensitive information and to ensure data quality and integrity by implementing effective data validation and cleansing techniques

POSITION REQUIREMENTS 

Required:

• Bachelor’s degree in Computer Science, Computer Engineering, or Information Technology or in lieu of a degree, at least 7 years of experience in data engineering
• 4-6+ years of data engineering experience.
• 2-4 years of experience with SQL including, but not limited to: PostgreSQL, T-SQL, PL/SQL, SNOWSQL
• 2-4+ years of experience with building applications, system integrations, and web services
• 2-4+ years of experience with server-side scripting and programming in a Linux environment (primarily bash shell)
• Advanced understanding of common database (Oracle, Snowflake) technologies including performance, tuning, and optimization.
• Advanced data manipulation skills and experience with on-prem and cloud-based data warehouse ETL tools and processes
• Basic understanding of business processes such as OTC, P2P, PIM to understand context of data usage

Preferred:

• 5+ years of experience with both cloud-based and on-prem OLTP database applications like MariaDB/MySQL, Oracle 19c+, etc
• Experience supporting micro-services applications through building data processes, designing data structures, performance tuning, supporting data transformations, syncing, metadata, dependencies, and workload management.
• Experience with CI/CD pipelines and workflows, including data/SQL script management tools like Liquibase

Technical Skills 

• Data security
• Automated testing tools
• Version control tools
• Data modeling