Data Observability Engineer

Sherwin-Williams•Cleveland, OH

2d•Onsite

About The Position

The Data Observability Engineer supports the design, development, and maintenance of systems and infrastructure that enable organizations to collect, store, process, and analyze large volumes of data. The role collaborates with data scientists, analysts, QA engineers, business process and functional SMEs, and other stakeholders to ensure data is accessible, reliable, and secure. Work includes data ingestion, transformation, integration, pipeline development, data governance, and software development and deployment of IT operations to shorten delivery and time to market for data products, pipelines, and data warehousing. The position is based at the company’s Cleveland Headquarters office and is not hybrid or remote. It involves contact with employees and access to confidential and proprietary information or other items of value. The company has determined that a criminal history review is necessary to protect its business, operations, reputation, staff, employees, and business relationships. Applicants must be at least 18 years old and legally authorized to work in the country of employment without current or future employment visa sponsorship.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, or Information Technology, or at least 3 years of data engineering experience in lieu of a degree.
At least 2 years of data engineering experience.
At least 2 years of SQL experience, including PostgreSQL, T-SQL, PL/SQL, or SnowSQL.
At least 1 year of experience building applications, system integrations, and web services.
At least 1 year of experience with server-side scripting and programming in a Linux environment, primarily using the Bash shell.
Experience with common database technologies such as Oracle and Snowflake, including performance tuning and optimization.
Data manipulation skills and experience with on-premises and cloud-based data warehouse ETL tools and processes.
Experience with version control tools.
Data modeling experience.
Must be at least 18 years of age.
Must be legally authorized to work in the country of employment without needing employment visa sponsorship now or in the future.

Nice To Haves

At least 2 years of hands-on experience building monitoring, alerting, or observability for data or application pipelines; experience with Splunk, Datadog, Dynatrace, Grafana, Prometheus, or ELK qualifies.
Experience with data quality or data observability frameworks, such as freshness, volume, and schema-drift checks.
Experience with log aggregation and parsing, metrics collection, and dashboard design.

Responsibilities

Collaborate with a team of data engineers, providing and seeking technical guidance, mentorship, and support.
Act as a technical point of contact for clients and stakeholders, providing updates and addressing 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.
Optimize data storage, processing, and retrieval mechanisms for performance and scalability.
Assist with technical leadership and guidance in selecting and implementing data engineering tools and technologies.
Identify and implement best practices and standards for data engineering processes and tools.
Keep up with emerging data engineering technologies and trends and evaluate their potential impact on the data infrastructure.
Collaborate with cross-functional teams to integrate data sources and enable seamless data flow across systems.
Work with data scientists, analysts, and stakeholders to understand data requirements and develop scalable data solutions.
Support implementation and maintenance of data governance and security measures to protect sensitive information.
Ensure data quality and integrity by implementing data validation and cleansing techniques.