Job Description

Job Title: Azure DataOps Lead

Department:

Managed Services - DataOps

Location:

Remote (India)

Reports To:

Data Engineering Manager - DataOps

Role Overview

The

Azure DataOpsLeadwill

be 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.