Data Operations Engineer II

About the role

AccuWeather Careers is hiring a Data Operations Engineer II to support the company's data infrastructure and operational workflows across its weather forecasting platform. This role focuses on maintaining, monitoring, and improving the systems that process and deliver weather data to internal teams and external customers worldwide. The engineer will work closely with data engineering and analytics teams to ensure that data pipelines run reliably and that data quality standards are consistently met across the organization. The position is based in State College, Pennsylvania or can be performed remotely, offering flexibility in how and where the day-to-day work is completed.

Key facts

What you'll do

Monitor data pipelines and workflows to identify failures, bottlenecks, or anomalies in processing jobs across production systems.

Maintain and update automated data validation checks that ensure accuracy and consistency across all ingested weather datasets.

Collaborate with data engineering and analytics teams to troubleshoot issues that arise in production data environments.

Document operational procedures, runbooks, and incident response steps for all data systems and supporting workflows.

Build and improve monitoring dashboards that track data freshness, volume, and quality metrics in real time.

Coordinate with external data providers to resolve ingestion errors, format compatibility issues, and data delivery problems.

Participate in on-call rotations to respond to data outages, degradation, or service interruptions outside normal business hours.

Write and maintain Python scripts that automate routine data operations tasks and reduce the need for manual intervention.

Review data flow architectures and propose concrete improvements that increase system reliability and reduce processing latency.

Assist in the planning and execution of data system upgrades, migrations, schema changes, and configuration updates.

Investigate and resolve data discrepancies reported by downstream consumers, including analysts and business stakeholders.

Optimize existing data workflows for performance, reliability, and cost efficiency within cloud-based data platforms.

Requirements

Bachelor's degree in computer science, engineering, or a related technical field is required for this position.

At least two years of experience working with data pipelines, ETL processes, or data operations in a professional setting.

Proficiency in Python or a similar scripting language for automating data workflows, scheduling tasks, and building operational tools.

Experience with SQL and working with relational databases in a production or staging environment on a regular basis.

Familiarity with cloud platforms such as AWS, Azure, or Google Cloud and their respective data services offerings.

Strong understanding of data quality principles, validation techniques, and monitoring strategies for large-scale data systems.

Ability to communicate technical findings clearly to both engineering colleagues and non-technical stakeholders across the organization.

Willingness to participate in on-call rotations and respond to incidents during evenings, weekends, or holidays as needed.

Nice to have

Experience with Apache Airflow, Luigi, or other workflow orchestration tools for scheduling and managing data pipeline jobs.

Knowledge of containerization technologies like Docker and orchestration platforms such as Kubernetes for deploying data applications.

Prior exposure to weather data formats, geospatial data standards, or meteorological data systems and conventions.

Comfort with version control systems, particularly Git, for managing infrastructure-as-code configurations and collaborative development workflows.

Familiarity with data modeling techniques and dimensional modeling concepts used in analytics and reporting environments.

Experience with CI/CD pipelines and automated testing frameworks for data engineering code and configuration changes.

Skills & tools

Python scripting for data automation, operational tasks, and building internal tooling to support data workflows.

SQL for querying, transforming, and manipulating data in relational databases used across the organization.

Cloud data services on AWS, Azure, or Google Cloud platforms, including storage and compute offerings.

Workflow orchestration tools such as Apache Airflow or equivalent scheduling systems for managing data job dependencies.

Monitoring and observability tools for tracking data pipeline health, performance metrics, and service availability.

Docker and container-based deployment practices for packaging, testing, and running data applications in production.

Git and version control workflows for managing code, configurations, and infrastructure-as-code definitions.

Data quality frameworks and validation libraries used to ensure accuracy across ingested and processed datasets.

Practical notes

This role is eligible for remote work or on-site presence at the State College, Pennsylvania office location.

The position follows a full-time schedule with standard business hours, though on-call duties may require evening or weekend availability during certain periods.

Candidates should expect to participate in regular team meetings, standups, and cross-functional collaboration sessions throughout each work week.

AccuWeather Careers offers a competitive benefits package; specific compensation details are available during the interview and offer stages.

The hiring process may include technical assessments, system design discussions, and interviews with data engineering team members.

This is a full-time position with opportunities for professional development and growth within the data operations organization.