Data Engineering Service Manager

Manager

Key Responsibilities

Service Leadership

• Own the end-to-end data engineering service lifecycle, ensuring high availability, reliability, and performance.
• Define and enforce SLAs, KPIs, and service health metrics for data engineering operations.
• Lead incident, problem, and change management processes aligned with ITIL best practices.
• Act as the primary escalation point for service issues and communicate effectively with stakeholders.
• Maintain service documentation, runbooks, and operational standards.
• Develop DevOps Automation, behaviours and practices
• Design and implement CI/CD pipelines for data engineering workflows (ETL/ELT, streaming, batch jobs).
• Automate deployment processes for data pipelines and related components.
• Manage version control, release management, and environment consistency.
• Integrate automated testing, monitoring, and alerting into data engineering workflows.
• Champion Infrastructure as Code (IaC) for provisioning and managing environments.
• Develop and enforce Governance & Compliance
• Ensure adherence to data governance, security, and compliance standards.
• Implement robust access controls and auditing for data engineering services.
• Drive Continuous Improvement
• Drive adoption of DevOps best practices within data engineering teams.
• Identify opportunities for automation and operational efficiency.
• Collaborate with engineering and architecture teams to improve delivery speed and reliability.

 

Required Qualifications

• Strong experience in service management (ITIL or similar frameworks).
• Proven track record in DevOps automation for data engineering (Databricks) or software delivery.
• Expertise in CI/CD tools (Azure DevOps, GitHub Actions, Jenkins, or similar).
• Proficiency in scripting languages (SQL, Python, PowerShell, Bash) for automation.
• Familiarity with Infrastructure as Code (Terraform, ARM templates, or similar).
• Experience working in Agile/Scrum environments.
• Excellent stakeholder management and communication skills.

 

Preferred Skills

• Experience in managing enterprise-scale data engineering services.
• Certifications in ITIL, DevOps, or cloud technologies.
• Knowledge of monitoring and observability tools 
• Familiarity with Microsoft Fabric and evolving Power BI ecosystem.
• Exposure to data governance, metadata management, and data cataloging tools.

Key Responsibilities

Service Leadership

• Own the end-to-end data engineering service lifecycle, ensuring high availability, reliability, and performance.
• Define and enforce SLAs, KPIs, and service health metrics for data engineering operations.
• Lead incident, problem, and change management processes aligned with ITIL best practices.
• Act as the primary escalation point for service issues and communicate effectively with stakeholders.
• Maintain service documentation, runbooks, and operational standards.
• Develop DevOps Automation, behaviours and practices
• Design and implement CI/CD pipelines for data engineering workflows (ETL/ELT, streaming, batch jobs).
• Automate deployment processes for data pipelines and related components.
• Manage version control, release management, and environment consistency.
• Integrate automated testing, monitoring, and alerting into data engineering workflows.
• Champion Infrastructure as Code (IaC) for provisioning and managing environments.
• Develop and enforce Governance & Compliance
• Ensure adherence to data governance, security, and compliance standards.
• Implement robust access controls and auditing for data engineering services.
• Drive Continuous Improvement
• Drive adoption of DevOps best practices within data engineering teams.
• Identify opportunities for automation and operational efficiency.
• Collaborate with engineering and architecture teams to improve delivery speed and reliability.

 

Required Qualifications

• Strong experience in service management (ITIL or similar frameworks).
• Proven track record in DevOps automation for data engineering (Databricks) or software delivery.
• Expertise in CI/CD tools (Azure DevOps, GitHub Actions, Jenkins, or similar).
• Proficiency in scripting languages (SQL, Python, PowerShell, Bash) for automation.
• Familiarity with Infrastructure as Code (Terraform, ARM templates, or similar).
• Experience working in Agile/Scrum environments.
• Excellent stakeholder management and communication skills.

 

Preferred Skills

• Experience in managing enterprise-scale data engineering services.
• Certifications in ITIL, DevOps, or cloud technologies.
• Knowledge of monitoring and observability tools 
• Familiarity with Microsoft Fabric and evolving Power BI ecosystem.
• Exposure to data governance, metadata management, and data cataloging tools.

Key Responsibilities

Service Leadership

• Own the end-to-end data engineering service lifecycle, ensuring high availability, reliability, and performance.
• Define and enforce SLAs, KPIs, and service health metrics for data engineering operations.
• Lead incident, problem, and change management processes aligned with ITIL best practices.
• Act as the primary escalation point for service issues and communicate effectively with stakeholders.
• Maintain service documentation, runbooks, and operational standards.
• Develop DevOps Automation, behaviours and practices
• Design and implement CI/CD pipelines for data engineering workflows (ETL/ELT, streaming, batch jobs).
• Automate deployment processes for data pipelines and related components.
• Manage version control, release management, and environment consistency.
• Integrate automated testing, monitoring, and alerting into data engineering workflows.
• Champion Infrastructure as Code (IaC) for provisioning and managing environments.
• Develop and enforce Governance & Compliance
• Ensure adherence to data governance, security, and compliance standards.
• Implement robust access controls and auditing for data engineering services.
• Drive Continuous Improvement
• Drive adoption of DevOps best practices within data engineering teams.
• Identify opportunities for automation and operational efficiency.
• Collaborate with engineering and architecture teams to improve delivery speed and reliability.

 

Required Qualifications

• Strong experience in service management (ITIL or similar frameworks).
• Proven track record in DevOps automation for data engineering (Databricks) or software delivery.
• Expertise in CI/CD tools (Azure DevOps, GitHub Actions, Jenkins, or similar).
• Proficiency in scripting languages (SQL, Python, PowerShell, Bash) for automation.
• Familiarity with Infrastructure as Code (Terraform, ARM templates, or similar).
• Experience working in Agile/Scrum environments.
• Excellent stakeholder management and communication skills.

 

Preferred Skills

• Experience in managing enterprise-scale data engineering services.
• Certifications in ITIL, DevOps, or cloud technologies.
• Knowledge of monitoring and observability tools 
• Familiarity with Microsoft Fabric and evolving Power BI ecosystem.
• Exposure to data governance, metadata management, and data cataloging tools.

Experience Level

Mid Level