TechOps - CloudOps - DataOps - Senior Professional
Ernst Young · Thiruvananthapuram · onsite · Posted today
About a minute. You'll make an account on the way through.
About this role
Job Summary
We are looking for a seasoned and proactive Senior DataOps Engineer to lead and manage data operations across modern Azure/AWS based data platforms. In this role, you will take ownership of mission-critical data pipelines, contribute to reliability engineering initiatives, and guide the continuous improvement of data ingestion, transformation, and monitoring processes. You will collaborate with cross-functional teams to drive operational excellence, troubleshoot complex issues, and help shape our DataOps strategy.
Your key responsibilities
- Ensure reliability and operational stability of enterprise data pipelines through proactive monitoring, incident management, troubleshooting, and continuous improvement across cloud data platforms.
- Lead the root cause analysis of recurring incidents, implement preventive actions, and establish best practices to improve system resilience.
- Mentor junior engineers and guide them in incident resolution, automation, and process standardization
- Collaborate with Data Engineering, DevOps, and Analytics teams to support production deployments and performance optimization.
- Proactively identify gaps in data and operational workflows and implement scalable solutions using scripting, automation, AI-assisted capabilities, Agentic AI patterns, and CI/CD practices.
- Drive improvements in operational processes by maintaining and enhancing runbooks, SOPs, and knowledge bases.
- Ensure compliance with data governance, logging, observability, and security best practices.
- Participate in rotational on-call duties and act as a point of escalation for complex operational issues
- Responsible for decision-making, optimizing processes, resource management, and overseeing team management as needed for task execution.
- Accountable for allocating personnel, supervising team members, assigning tasks, ensuring that the team has the necessary tools and support to succeed in their roles and optimizing and evaluating their performance to meet organizational goals.
Skills and attributes for success
- Deep understanding of cloud data services (Databricks, Snowflake, Data lakes, Informatica) and data engineering operational models.
- Solid understanding of ETL/ELT design and implementation principles.
- Strong SQL and PySpark skills for data transformation and validation.
- Strong problem-solving and analytical skills with a focus on proactive incident prevention.
- Experience building or supporting Agentic AI solutions integrated with enterprise data platforms, APIs, databases, or operational tools.
- Experience architecting AI agents for operational use cases such as incident triage, root cause analysis, data quality investigation etc.
- Ability to identify opportunities to apply AI-assisted automation within DataOps, improving monitoring, incident resolution, operational efficiency, and engineering productivity.
- Excellent communication and stakeholder collaboration abilities across distributed teams
- Leadership mindset with experience mentoring team members or guiding junior staff
- Attention to detail and a strong commitment to quality and documentation
To qualify for the role, you must have
- Bachelor s degree in computer science and engineering, Data Analytics, or a related field, or equivalent work experience
- 5-8 years of experience working in data operations, data engineering support, or application management roles
- Strong experience supporting and maintaining cloud-based data pipelines, data storage and processing platforms, with hands-on experience in Databricks and Informatica.
- Expertise in root cause analysis, incident resolution, and monitoring for large-scale data workflows
- Experience with CI/CD tools like Azure DevOps, Git, and deployment automation
- Proficiency in SQL and scripting languages such as Python or PySpark
- Solid understanding of data governance, performance tuning, and cloud-based data architecture best practices.
- Experience in global delivery models and distributed teams.
- Excellent stakeholder collaboration skills to translate business needs into scalable technical solutions.
- Willingness to participate in 24/7 support rotations or cover critical business hours
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Skills
About Ernst & Young

Ernst Young
Management Consulting
44k+
employees
2002
24 years old
Gurgaon / Gurugram, Haryana
India
₹15.3L PA avg
Avg at Ernst & Young
About
Industries
Employee ratings
10 reviews
Culture
1.9
Career growth
2.3
Work-life
2.5
Employees rate it well for
Find them on
Career guides
- How to Build a Job Application Automation in 2026: Architecture, ATS APIs and Code - and When to Buy Instead
- AI Bots That Fill Job Applications and Answer Screening Questions (2026): 8 Tools Compared on CTC, Notice Period and Knockout Questions
- Does Auto-Apply Hurt Your Chances? What the Callback Data Says, and Safe Limits (2026)