DataOps Engineer

Experience:
5-8yrs

Location:
Bangalore / Chennai / Hyderabad / Gurgaon/ Pune / Kolkata Role Overview We are seeking experienced DataOps Engineers to ensure our data platforms remain reliable, observable, secure, and production ready. This role bridges Data Engineering, Operations, Site Reliability Engineering (SRE), and Platform Operations, with a strong focus on operational excellence and continuous improvement. You will be responsible for building and maintaining observability solutions, managing incidents, developing operational processes, and enabling support teams. A key expectation is to embed operational readiness into the software delivery lifecycle through a shift-left approach, ensuring that monitoring, supportability, automation, and resilience are designed into solutions from the outset rather than addressed after production deployment. This is a highly hands-on role requiring close collaboration with engineering, support, platform, and business teams. Candidates should be comfortable articulating technical decisions, operational trade-offs, and business impact to both technical and non-technical stakeholders.

Key Responsibilities
• Design, implement, and maintain monitoring, alerting, observability frameworks, and operational dashboards for data platforms and pipelines using tools such as Datadog, Splunk, CloudWatch, or equivalent.
• Own the end-to-end incident management lifecycle, including detection, triage, escalation, communication, resolution, root cause analysis (RCA), and post-incident reviews.
• Develop and maintain runbooks, operational playbooks, knowledge articles, and troubleshooting guides; enable L1/L2 support teams through training and knowledge transfer.
• Embed shift-left operational readiness into CI/CD processes, including observability standards,



automated operational checks, deployment validation, release readiness reviews, and support handovers.
• Build and maintain integrations using REST APIs, ServiceNow, OKTA, and other enterprise platforms to automate operational workflows, ticket routing, access management, and alert remediation.
• Troubleshoot, optimize, and improve the performance, reliability, and scalability of data workloads, including Databricks jobs, SQL workloads, and data pipelines.
• Define, measure, and continuously improve operational metrics and service reliability indicators, including SLAs, SLOs, MTTD, MTTR, incident trends, and platform availability.
• Collaborate closely with Data Engineers, Architects, Product Owners, Platform/DevOps teams, and business stakeholders to ensure operational excellence across the platform landscape.
• Document platform architecture, system dependencies, data flows, operational procedures, and support processes to ensure maintainability and knowledge sharing.
• Contribute to platform reliability initiatives by implementing automation, resiliency patterns, self-healing mechanisms, and operational best practices. Required Qualifications
• 4+ years of experience in Data Operations, DataOps, SRE, Production Support, or Platform Operations roles.
• Strong hands-on experience with at least one enterprise monitoring platform such as Datadog, Splunk, CloudWatch, Dynatrace, or New Relic.




• 2+ years of experience in incident management, operational support, runbook development, and support team enablement.
• Experience building integrations using REST APIs, ServiceNow, OKTA, or similar enterprise platforms.
• Proven experience implementing operational readiness and observability practices within software delivery pipelines.
• Strong working knowledge of SQL and Databricks, including troubleshooting, debugging, and performance optimization.
• Experience defining and tracking operational KPIs, reliability metrics, and service-level objectives.
• Ability to clearly explain system architecture, data flows, design decisions, operational risks, and business impact.
• Robust stakeholder management and communication skills, particularly during incident and escalation scenarios. Preferred Skills
• Experience with DevOps, Platform Operations, or Site Reliability Engineering (SRE) practices.
• Hands-on experience with CI/CD tools such as Azure DevOps, GitHub Actions, Jenkins, GitLab CI/CD, or similar platforms.
• Experience with Infrastructure as Code (IaC) tools such as Terraform, ARM Templates, CloudFormation, or Bicep.
• Automation and scripting skills using Python, PowerShell, Bash, or Shell scripting.
• Cloud platform experience in AWS, Azure, or GCP, including monitoring and operational tooling.
• Familiarity with container and orchestration technologies such as Docker and Kubernetes.
• Experience supporting enterprise platforms, platform engineering teams, or shared services environments.
• Familiarity with ITIL processes, Service Management practices, and on-call support models.
• Experience with data observability, lineage, governance, and data quality tooling.

📌 Senior DataOps Engineer (Bengaluru)
🏢 Tredence
📍 Bengaluru