Azure DataOps Lead

Job Description

Job Title: Azure DataOps Lead

Department: Managed Services – DataOps Location: Remote (India) Reports To: Data Engineering Manager – DataOps

Role Overview

The Azure DataOpsLeadwillbe responsible for leading the operational delivery, automation, and governance of Azure-based data platforms for enterprise clients. This role involves managing L1/L2/L3 operations, driving proactive monitoring, ensuring SLA adherence, and enabling seamless collaboration between Data Engineering, Cloud, and Business teams.

The ideal candidate combines hands-on Azure Data Platform expertise, strong DataOps process management, and team leadership skills to ensure operational excellence, cost optimization, and continuous improvement across customer environments.

Key Responsibilities

• Lead and manage the Azure DataOps function, ensuring smooth daily operations, incident resolution, and performance stability across production data platforms.
• Oversee data pipeline orchestration and automation using Azure Data Factory (ADF), Synapse Analytics, Databricks, and Logic Apps.
• Implement CI/CD pipelines for data workflows using Azure DevOps or equivalent automation tools.
• Drive incident, problem, change, and request management processes aligned with ITIL best practices.
• Coordinate with L1/L2 support teams for escalations, RCA preparation, and client communication.
• Maintain governance for data quality, access control, and compliance using Azure Purview, Key Vault, and RBAC.
• Collaborate with Data Architects and Cloud Engineers to design scalable, resilient, and cost-efficient Azure data solutions.
• Ensure ²⁴⁄₇ operational readiness through proactive alert monitoring, performance tuning, and preventive maintenance.
• Contribute to automation initiatives using PowerShell, Python, or ARM templates to reduce manual efforts and improve system reliability.
• Partner with customer stakeholders to report on SLAs, KPIs, RCA summaries, and provide technical recommendations for improvement.
• Support onboarding and knowledge transition for new clients and ensure documentation consistency across environments.
• Mentor and upskill the DataOps L1/L2 teams, fostering a culture of ownership, accountability, and process discipline.

Required Skills & Experience

• 8–12 years of total IT experience with at least 3–5 years in Azure DataOps or Data Engineering leadership.
• Hands-on expertise with key Azure Data Services, including:
• Azure Data Factory (ADF)
• Azure Synapse Analytics
• Azure Databricks
• Azure SQL Database / SQL Managed Instance
• Azure Data Lake Storage Gen2 (ADLS)
• Strong understanding of DataOps concepts
• Experience in monitoring and alerting using Log Analytics, Application Insights, and Azure Monitor.
• Working knowledge of incident management, RCA documentation, and operational reporting.
• Strong analytical skills for troubleshooting performance issues and identifying optimization opportunities.
• Excellent communication and stakeholder management skills across global teams.

Preferred Qualifications

• Microsoft Certified: Azure Data Engineer Associate
• Proficiency across the Azure stack, including Azure SQL Database, Azure Key Vault, Azure Monitor, and Azure Event Hub.
• Experience with Power BI, DataBricks Notebooks, or ML Ops pipelines is a plus.
• Experience working in managed services environments with ²⁴⁄₇ rotational support models.

Soft Skills

• Strong leadership with a proactive and analytical mindset.
• Effective communicator with the ability to manage global stakeholders.
• Team-oriented with a focus on mentoring and capability building.
• Process-driven approach with commitment to continuous improvement.
• Strong sense of accountability and delivery excellence.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.