Data Operations Engineer
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Job Description
Engineer supporting data operations and implementation of DataOps processes for the enterprise Snowflake data platform. Collaborates on reliability and governance while developing expertise in DataOps engineering.
Responsibilities:
- Supports the reliability, quality, governance, and operational effectiveness of the enterprise Snowflake data platform.
- Contributes to the implementation and maintenance of DataOps processes, automated testing, monitoring, deployment pipelines, and governance controls.
- Supports implementation of data contracts, schema standards, and release procedures for batch and streaming data products.
- Participates in validation of schema changes and assists with impact assessments.
- Maintains documentation related to data products, SLAs, and operational procedures.
- Contributes to Git-based deployment pipelines for Snowflake and dbt assets.
- Implements and maintains automated testing for data transformations and data quality checks.
- Supports promotion of code and configuration across development, testing, and production environments.
- Monitors scheduled data pipelines and investigates operational issues.
- Assists with implementation and maintenance of orchestration workflows using approved tools.
- Supports execution of operational runbooks and recovery procedures.
- Develops and maintains data quality tests and monitoring dashboards.
- Investigates anomalies and participates in issue resolution activities.
- Participates in on-call support and incident response activities.
- Monitors warehouse utilization and query performance metrics.
Requirements:
- Bachelor's degree in Computer Science, Information Systems, Data Analytics, or related field.
- 2–4 years of data engineering, analytics engineering, or platform operations experience.
- Experience with Snowflake, SQL, and data transformation frameworks.
- Exposure to Git-based development practices.
- Familiarity with data quality concepts and cloud data platforms.
- Experience with dbt and Terraform (preferred).
- Exposure to orchestration tools such as Airflow or Dagster (preferred).
- Experience supporting production data environments (preferred).
- Familiarity with governance and data catalog technologies (preferred).
Benefits:
- flexible work environment
- fluid career paths
- celebrate internal mobility
- purpose and well-being recognition
- work-life balance
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