Role Overview
We are seeking a Data Engineering Service & DevOps Lead to ensure operational excellence and drive automation across our data engineering services. This role combines service leadership—owning reliability, governance, and stakeholder engagement—with DevOps automation, enabling rapid, secure, and consistent delivery of data solutions.
We are seeking a highly experienced and strategic thinker with the ability to lead from the front. This role blends deep technical expertise with hands-on administration and platform governance, ensuring scalable, secure, and high-performing analytics delivery across the organization.
You will work closely with data engineers, analysts, and business stakeholders to ensure SLA are understood and met, while also developing and managing our DevOps processes.
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.
- 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.
- 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.
Required Qualifications
Preferred Skills
Role Overview
We are seeking a Data Engineering Service & DevOps Lead to ensure operational excellence and drive automation across our data engineering services. This role combines service leadership—owning reliability, governance, and stakeholder engagement—with DevOps automation, enabling rapid, secure, and consistent delivery of data solutions.
We are seeking a highly experienced and strategic thinker with the ability to lead from the front. This role blends deep technical expertise with hands-on administration and platform governance, ensuring scalable, secure, and high-performing analytics delivery across the organization.
You will work closely with data engineers, analysts, and business stakeholders to ensure SLA are understood and met, while also developing and managing our DevOps processes.
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.
- 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.
- 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.
Required Qualifications
Preferred Skills
Role Overview
We are seeking a Data Engineering Service & DevOps Lead to ensure operational excellence and drive automation across our data engineering services. This role combines service leadership—owning reliability, governance, and stakeholder engagement—with DevOps automation, enabling rapid, secure, and consistent delivery of data solutions.
We are seeking a highly experienced and strategic thinker with the ability to lead from the front. This role blends deep technical expertise with hands-on administration and platform governance, ensuring scalable, secure, and high-performing analytics delivery across the organization.
You will work closely with data engineers, analysts, and business stakeholders to ensure SLA are understood and met, while also developing and managing our DevOps processes.
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.
- 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.
- 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.
Required Qualifications
Preferred Skills