Overview
We’re looking for a DataOps Engineer to join one of our Data Platform teams. You’ll be responsible for building, automating, and optimizing the processes that enable reliable, scalable, and secure data delivery. You’ll work closely with Data Engineers, BI Developers, Data Scientists, DevOps Engineers, and Solution Architects to streamline data pipelines, automate deployments, improve observability, and ensure high-quality data operations across enterprise environments.
Requirements
DataOps & platform automation
- Design, implement, and maintain DataOps processes that support the development, deployment, and operation of enterprise data platforms.
- Automate data pipeline deployments and operational workflows across development, testing, and production environments.
- Develop reusable automation scripts and infrastructure components to improve delivery efficiency.
- Collaborate with Data Engineering teams to standardize deployment and operational practices.
- Define and promote DataOps standards, templates, and best practices.
- Maintain technical documentation for deployment processes, operational procedures, and platform configurations.
CI/CD & deployment
- Build and maintain CI/CD pipelines for data integration, analytics, and data platform components.
- Automate testing, deployment, and release management processes.
- Implement version control and branching strategies for data projects.
- Support environment management and deployment orchestration.
- Collaborate with development teams to improve release quality and reduce deployment risks.
- Troubleshoot deployment failures and optimize release processes.
Data pipelines & operations
- Monitor and maintain enterprise data pipelines to ensure availability, reliability, and performance.
- Identify, investigate, and resolve operational issues affecting data workflows.
- Implement scheduling, orchestration, and workflow automation for data processing.
- Optimize pipeline performance and resource utilization.
- Support incident management, root cause analysis, and operational improvements.
- Ensure operational processes meet agreed service levels and business requirements.
Monitoring, observability & data quality
- Implement monitoring, logging, and alerting for enterprise data platforms.
- Define operational KPIs and monitor platform health and data pipeline performance.
- Collaborate with Data Governance and Data Engineering teams to implement automated data quality controls.
- Support proactive detection of data anomalies and operational issues.
- Produce operational reports and recommend continuous improvements.
- Contribute to platform reliability and operational excellence initiatives.
Infrastructure & cloud platforms
- Support cloud-based data platforms and enterprise data infrastructure.
- Collaborate with DevOps and Infrastructure teams to provision and maintain environments.
- Implement Infrastructure as Code (IaC) where appropriate.
- Support platform scalability, security, backup, and disaster recovery processes.
- Ensure environments comply with enterprise security and governance standards.
- Participate in platform upgrades and technology modernization initiatives.
Desired profile
Must-have
- University degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field.
- 3+ years of experience in DataOps, Data Engineering, DevOps, or Data Platform Administration.
- Strong SQL skills and good understanding of data integration and data warehouse concepts.
- Experience with CI/CD tools such as Azure DevOps, GitHub Actions, GitLab CI/CD, or Jenkins.
- Experience with Git version control and collaborative development practices.
- Knowledge of scripting languages such as Python, PowerShell, or Bash.
- Familiarity with workflow orchestration tools such as Apache Airflow, Azure Data Factory, or similar.
- Strong analytical and troubleshooting skills.
- Excellent communication and collaboration abilities.
Nice to have
- Experience with Microsoft Fabric, Azure Synapse Analytics, Azure Data Factory, Databricks, Snowflake, or Microsoft SQL Server.
- Experience with Docker, Kubernetes, and Infrastructure as Code tools such as Terraform or Bicep.
- Familiarity with monitoring platforms such as Azure Monitor, Grafana, Prometheus, or Splunk.
- Experience working in cloud environments (Microsoft Azure, AWS, or Google Cloud).
- Experience in Banking, Retail, Insurance, or Telco industries.
- Microsoft Azure, Kubernetes, Terraform, or DevOps certifications.
How you work
- Passionate about automation and operational excellence.
- Strong ownership and attention to detail.
- Proactive in identifying opportunities for optimization.
- Comfortable working across development, operations, and business teams.
- Focused on reliability, scalability, and continuous improvement.
- Committed to delivering secure and maintainable data platforms.
Interested and suitable for this job?
Apply now for DataOps Engineer position