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Ernst & Young

Global professional services: consulting, assurance, tax

Techops – Senior - Cloudops, Dataops

Data EngineeringUpdated on Nov 14
Full-timeThiruvananthapuram, Kerala, IndiaNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in computer science and engineering, Data Analytics, or a related field, or equivalent work experience.
  • 5–8 years of experience in data operations, data engineering support, or application management roles.
  • Strong experience supporting and maintaining cloud-based data pipelines, data storage and processing platforms, including hands-on experience with Databricks and Informatica.
  • Expertise in root cause analysis, incident resolution, and monitoring for large-scale data workflows.
  • Experience with CI/CD tools such as Azure DevOps and Git, and deployment automation.
  • Experience building or supporting Agentic AI solutions integrated with enterprise data platforms, APIs, databases, or operational tools.
  • Proficiency in SQL and scripting languages such as Python or PySpark.
  • A solid understanding of data governance, performance tuning, and cloud-based data architecture best practices.
  • Experience in global delivery models and distributed teams.
  • Willingness to participate in 24/7 support rotations or cover critical business hours.
  • Strong hands-on experience with Data Factory, Data Lake or Amazon S3, Synapse or Redshift, Databricks, Snowflake, and Informatica.
  • Strong root cause analysis skills across data pipelines, storage layers, and reporting.
  • Hands-on scripting with Python or PySpark for automation or pipeline optimization.
  • Strong SQL skills for data analysis, issue diagnosis, and validation.
  • Experience architecting AI agents for operational use cases such as incident triage, root cause analysis, and data quality investigation.
  • Experience leading incident resolution calls and engaging with business stakeholders.
  • Ability to identify opportunities to apply AI-assisted automation within DataOps to improve monitoring, incident resolution, operational efficiency, and engineering productivity.
  • Ability to collaborate with Data Engineering, DevOps, and Analytics teams to support production deployments and performance optimization.
  • Ability to work in rotational shifts to support business-critical systems operating in a 24/7 environment.

Responsibilities

  • Ensure reliability and operational stability of enterprise data pipelines through proactive monitoring, incident management, troubleshooting, and continuous improvement across cloud data platforms.
  • Lead 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.
  • Identify gaps in data and operational workflows and implement scalable solutions using scripting, automation, AI-assisted capabilities, Agentic AI patterns, and CI/CD practices.
  • Maintain and enhance runbooks, standard operating procedures, and knowledge bases to improve operational processes.
  • Ensure compliance with data governance, logging, observability, and security best practices.
  • Participate in rotational on-call duties and act as an escalation point for complex operational issues.
  • Make decisions, optimize processes, manage resources, and oversee team management as needed for task execution.
  • Allocate personnel, supervise team members, assign tasks, provide necessary tools and support, and evaluate team performance to meet organizational goals.

Desired Qualifications

  • Experience integrating data from ERP, CRM, POS systems, or third-party APIs.
  • CI/CD experience using DevOps pipelines, repositories, and artifacts.
  • Hands-on exposure to enterprise AI development tools and frameworks such as Microsoft Foundry or Azure OpenAI, Microsoft Copilot Studio, LangChain, LangGraph, or equivalent technologies.
  • Familiarity with LLM or agent observability, evaluation, tracing, security guardrails, and responsible AI practices.
  • Certifications such as Azure or AWS Certified Data Engineer Associate, Databricks Certified Data Engineer Professional, Snowflake SnowPro Core Certification, or Informatica Cloud Data Integration Specialist.

About the Company

Ernst & Young

Global professional services: consulting, assurance, tax

EY (Ernst & Young) provides professional services at a global scale, offering consulting, assurance, tax, and transaction advisory services. It serves clients across industries such as technology, media, real estate, hospitality, and construction. Instead of selling a single product, EY works with clients through tailored engagements where cross-disciplinary teams analyze challenges, design strategies, perform audits, help with tax planning, and assist with mergers or divestitures. What sets EY apart is its worldwide reach and integrated service model, industry-specific expertise, and focus on responsible business practices like sustainability, cybersecurity, and workforce flexibility. EY’s goal is to help organizations improve performance, manage risk, and achieve sustainable growth while building a better working world.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Boston, MA
Founded
1991

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