Senior Data Platform Engineer

Start Date

Starts Immediately

CTC (ANNUAL)

Competitive salary Competitive salary

Experience

5 year(s)

Apply By

Not Provided

Posted 3 weeks ago

Job

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About the job

Kenvue is currently recruiting for a:

Senior Data Platform Engineer

What we do

At Kenvue , we realize the extraordinary power of everyday care. Built on over a century of heritage and rooted in science, were the house of iconic brands - including NEUTROGENA, AVEENO, TYLENOL, LISTERINE, JOHNSONS and BAND-AID that you already know and love. Science is our passion; care is our talent.

Who We Are

Our global team is ~ 22,000 brilliant people with a workplace culture where every voice matters, and every contribution is appreciated. We are passionate about insights, innovation and committed to delivering the best products to our customers. With expertise and empathy, being a Kenvuer means having the power to impact millions of people every day. We put people first, care fiercely, earn trust with science and solve with courage and have brilliant opportunities waiting for you! Join us in shaping our futureand yours. For more information , click here .

Role reports to:

Enterprise Integration Lead

Location:

Asia Pacific, India, Karnataka, Bangalore

Work Location:

Hybrid

What you will do

Senior Software Engineer - Data Platform Engineering

Role Overview

We are seeking a Senior Software Engineer to build, automate, and operate enterprise-scale data platforms powered by Databricks, Snowflake, Microsoft Fabric, Kubernetes, and cloud-native technologies . This role focuses on platform engineering, DevOps automation, reliability, observability, security, and self-service enablement for data engineering and analytics teams.

The ideal candidate will have strong experience managing modern data platforms, implementing Infrastructure as Code, automating deployments, optimizing platform performance, and ensuring operational excellence across cloud-based environments.

Key Responsibilities

Data Platform Engineering

Design, implement, and support enterprise data platforms based on Databricks, Snowflake, and Microsoft Fabric.
Build reusable platform capabilities enabling self-service onboarding, provisioning, monitoring, and governance.
Standardize platform architecture, deployment patterns, and operational processes.
Support multi-environment strategies (Development, QA, Production).

Kubernetes & Cloud Infrastructure

Build and manage Kubernetes-based platform services supporting data processing workloads.
Deploy and operate containerized applications and platform services using Kubernetes.
Implement auto-scaling, high availability, disaster recovery, and resiliency patterns.
Manage infrastructure through Infrastructure as Code (Terraform, Bicep, Helm).

DevOps & Platform Automation

Develop CI/CD pipelines for platform deployment and configuration management.
Automate provisioning of Databricks workspaces, Snowflake objects, Fabric resources, and Kubernetes infrastructure.
Implement GitOps and automated release management practices.
Build platform automation frameworks to reduce manual operational effort.

Reliability Engineering & Operations

Establish monitoring, observability, and alerting across platform components.
Drive platform reliability, stability, and performance improvements.
Perform root cause analysis and remediation of platform incidents.
Support production operations and critical issue resolution.

Security & Governance

Implement platform security controls, RBAC, secrets management, and network security.
Ensure compliance with enterprise governance standards.
Support metadata management, auditing, lineage, and monitoring controls.
Partner with cybersecurity teams to address platform vulnerabilities and risks.

Cost Optimization & Capacity Management

Optimize Databricks clusters, Snowflake warehouses, Fabric capacities, and Kubernetes resources.
Monitor platform utilization and recommend cost-saving opportunities.
Implement FinOps practices and governance guardrails.

Required Qualifications

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
5-7 years of experience in Platform Engineering, DevOps, Cloud Engineering, or Data Platform Operations.
Strong experience supporting Databricks, Snowflake, or Microsoft Fabric platforms.
Experience managing Kubernetes-based workloads in production environments.
Hands-on experience with CI/CD, Infrastructure as Code, and cloud-native architectures.
Strong scripting and automation experience using Python, PowerShell, Bash, or similar languages.
Experience working within Agile and DevOps delivery models.

Required Technical Skills

Data Platforms

Databricks
Snowflake
Microsoft Fabric
Delta Lake
Data Lakehouse Architecture

Kubernetes & Containers

Kubernetes
Docker
Helm
Kustomize
Container Lifecycle Management

DevOps & Automation

Azure DevOps
GitHub Actions
Jenkins
Git
CI/CD Pipelines

Infrastructure as Code

Terraform
Bicep
ARM Templates
Infrastructure Automation

Cloud Platforms

Microsoft Azure (Preferred)
AWS or GCP Exposure

Monitoring & Observability

Prometheus
Grafana
Azure Monitor
Log Analytics
OpenTelemetry

Platform Security

RBAC
Azure AD / Entra ID
Secret Management
Key Vault
Security Automation

Programming

Python
SQL
PowerShell
Bash

Preferred Qualifications

Databricks Certified Data Engineer or Platform Administrator.
SnowPro Certification.
Microsoft Fabric Certification.
Certified Kubernetes Administrator (CKA).
Terraform Associate Certification.
Experience with: Apache Airflow Kafka Spark on Kubernetes Kyuubi GitOps ArgoCD Service Mesh Platform SRE Practices

If you are an individual with a disability, please check our Disability Assistance page for information on how to request an accommodation.

Earn certifications in these skills

+ 5 more skills

Who can apply

Only those candidates can apply who:

1. have minimum 5 years of experience

Salary

Probation:

Duration:

Salary during probation:

After probation:

Annual CTC: Competitive salary

Number of openings

Editor’s note

Information above is Internshala's interpretation and paraphrasing of what we found on the shared link.

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