Data Observability Engineer

The Data Engineer is responsible for supporting in the designing, building, and maintaining of 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. 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.

• Collaborate with a team of data engineers, seeking and 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

• Assist in providing 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

• Support in the implementation and maintenance of data governance and security measures to protect sensitive information and to ensure data quality and integrity by implementing effective data validation and cleansing techniques

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

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.

Must be eighteen years or older

EDUCATION AND EXPERIENCE

Required

• Bachelor’s degree in Computer Science, Computer Engineering, or Information Technology or in lieu of a degree, at least 3 years of experience in data engineering.
• 2+ years of data engineering experience.
• 2+ years of experience with SQL including, but not limited to: PostgreSQL, T-SQL, PL/SQL, SNOWSQL
• 1+ years of experience with building applications, system integrations, and web services
• 1+ years of experience with server-side scripting and programming in a Linux environment (primarily bash shell)
• Experience with common database (Oracle, Snowflake) technologies including performance, tuning, and optimization.
• Data manipulation skills and experience with on-prem and cloud-based data warehouse ETL tools and processes
• Version control tools
• Data modeling
• Must be at least 18 years of age
• Must be legally authorized to work in the country of employment without needing sponsorship for employment work visa status now or in the future.

Preferred

• 2+ years of hands-on experience building monitoring, alerting, or observability for data or application pipelines. Experience with any of Splunk, Datadog, Dynatrace, Grafana, Prometheus, or ELK qualifies. We value the concepts over the specific tool.
• Experience with data quality or data observability frameworks (for example, freshness, volume, and schema-drift checks).
• Experience with log aggregation and parsing, metrics collection, and dashboard design.