DataOps Specialist

About the role

The DataOps Specialist ensures that data pipelines, analytics workloads, and AI models run reliably in production. This role combines engineering, operations, and monitoring to deliver automated, repeatable, and supportable data services.

Key responsibilities

• Support reliable operation of data pipelines, jobs, workflows, and data quality checks.
• Monitor scheduled workloads, handle failures, delays, alerts, and track operational trends.
• Assist with deployment, release management, environment promotion, and configuration control.
• Implement automation for repeatable data‑operations tasks and maintain operational runbooks.
• Provide logging, monitoring, observability, and alerting for data workflows.
• Investigate pipeline failures, job errors, performance issues, and coordinate resolution across engineering, platform, security, and support teams.
• Maintain documentation such as support guides, escalation procedures, and known‑issue records.
• Participate in production readiness reviews, service transition, hyper‑care, and business‑as‑usual handover.

Required profile

• Hands‑on experience with data pipelines, ETL/ELT processes, and analytics platforms.
• Strong troubleshooting skills for SQL, data validation, reconciliation, and performance problems.
• Ability to work effectively with data engineering, platform, security, infrastructure, and business teams.
• Understanding of incident, change, problem management, and production support practices.

Required skills

• Airflow, Control‑M, Azure Data Factory, Informatica, dbt Cloud, Dagster, Prefect (or equivalent orchestration tools)
• CI/CD, version control, release management
• Monitoring, logging, alerting, operational dashboards
• SQL and data troubleshooting
• Data validation, reconciliation, data quality checks
• Azure, AWS, Google Cloud, Snowflake, Databricks, SQL Server, Oracle
• Python, Bash, PowerShell (scripting/automation)