3+ ECS Jobs in Delhi, NCR and Gurgaon | ECS Job openings in Delhi, NCR and Gurgaon

Required Skills: Advanced AWS Infrastructure Expertise, CI/CD Pipeline Automation, Monitoring, Observability & Incident Management, Security, Networking & Risk Management, Infrastructure as Code & Scripting

Criteria:

• 5+ years of DevOps/SRE experience in cloud-native, product-based companies (B2C scale preferred)
• Strong hands-on AWS expertise across core and advanced services (EC2, ECS/EKS, Lambda, S3, CloudFront, RDS, VPC, IAM, ELB/ALB, Route53)
• Proven experience designing high-availability, fault-tolerant cloud architectures for large-scale traffic
• Strong experience building & maintaining CI/CD pipelines (Jenkins mandatory; GitHub Actions/GitLab CI a plus)
• Prior experience running production-grade microservices deployments and automated rollout strategies (Blue/Green, Canary)
• Hands-on experience with monitoring & observability tools (Grafana, Prometheus, ELK, CloudWatch, New Relic, etc.)
• Solid hands-on experience with MongoDB in production, including performance tuning, indexing & replication
• Strong scripting skills (Bash, Shell, Python) for automation
• Hands-on experience with IaC (Terraform, CloudFormation, or Ansible)
• Deep understanding of networking fundamentals (VPC, subnets, routing, NAT, security groups)
• Strong experience in incident management, root cause analysis & production firefighting

Description

Role Overview

Company is seeking an experienced Senior DevOps Engineer to design, build, and optimize cloud infrastructure on AWS, automate CI/CD pipelines, implement monitoring and security frameworks, and proactively identify scalability challenges. This role requires someone who has hands-on experience running infrastructure at B2C product scale, ideally in media/OTT or high-traffic applications.

 Key Responsibilities

1. Cloud Infrastructure — AWS (Primary Focus)

• Architect, deploy, and manage scalable infrastructure using AWS services such as EC2, ECS/EKS, Lambda, S3, CloudFront, RDS, ELB/ALB, VPC, IAM, Route53, etc.
• Optimize cloud cost, resource utilization, and performance across environments.
• Design high-availability, fault-tolerant systems for streaming workloads.

2. CI/CD Automation

• Build and maintain CI/CD pipelines using Jenkins, GitHub Actions, or GitLab CI.
• Automate deployments for microservices, mobile apps, and backend APIs.
• Implement blue/green and canary deployments for seamless production rollouts.

3. Observability & Monitoring

• Implement logging, metrics, and alerting using tools like Grafana, Prometheus, ELK, CloudWatch, New Relic, etc.
• Perform proactive performance analysis to minimize downtime and bottlenecks.
• Set up dashboards for real-time visibility into system health and user traffic spikes.

4. Security, Compliance & Risk Highlighting

• Conduct frequent risk assessments and identify vulnerabilities in:

  o Cloud architecture

  o Access policies (IAM)

  o Secrets & key management

  o Data flows & network exposure

• Implement security best practices including VPC isolation, WAF rules, firewall policies, and SSL/TLS management.

5. Scalability & Reliability Engineering

• Analyze traffic patterns for OTT-specific load variations (weekends, new releases, peak hours).
• Identify scalability gaps and propose solutions across:
•   o Microservices
•   o Caching layers
•   o CDN distribution (CloudFront)
•   o Database workloads
• Perform capacity planning and load testing to ensure readiness for 10x traffic growth.

6. Database & Storage Support

• Administer and optimize MongoDB for high-read/low-latency use cases.
• Design backup, recovery, and data replication strategies.
• Work closely with backend teams to tune query performance and indexing.

7. Automation & Infrastructure as Code

• Implement IaC using Terraform, CloudFormation, or Ansible.
• Automate repetitive infrastructure tasks to ensure consistency across environments.

Required Skills & Experience

Technical Must-Haves

• 5+ years of DevOps/SRE experience in cloud-native, product-based companies.
• Strong hands-on experience with AWS (core and advanced services).
• Expertise in Jenkins CI/CD pipelines.
• Solid background working with MongoDB in production environments.
• Good understanding of networking: VPCs, subnets, security groups, NAT, routing.
• Strong scripting experience (Bash, Python, Shell).
• Experience handling risk identification, root cause analysis, and incident management.

Nice to Have

• Experience with OTT, video streaming, media, or any content-heavy product environments.
• Familiarity with containers (Docker), orchestration (Kubernetes/EKS), and service mesh.
• Understanding of CDN, caching, and streaming pipelines.

Personality & Mindset

• Strong sense of ownership and urgency—DevOps is mission critical at OTT scale.
• Proactive problem solver with ability to think about long-term scalability.
• Comfortable working with cross-functional engineering teams.

Why Join company?

• Build and operate infrastructure powering millions of monthly users.

• Opportunity to shape DevOps culture and cloud architecture from the ground up.

• High-impact role in a fast-scaling Indian OTT product.

Review Criteria

• Strong MLOps profile
• 8+ years of DevOps experience and 4+ years in MLOps / ML pipeline automation and production deployments
• 4+ years hands-on experience in Apache Airflow / MWAA managing workflow orchestration in production
• 4+ years hands-on experience in Apache Spark (EMR / Glue / managed or self-hosted) for distributed computation
• Must have strong hands-on experience across key AWS services including EKS/ECS/Fargate, Lambda, Kinesis, Athena/Redshift, S3, and CloudWatch
• Must have hands-on Python for pipeline & automation development
• 4+ years of experience in AWS cloud, with recent companies
• (Company) - Product companies preferred; Exception for service company candidates with strong MLOps + AWS depth

Preferred

• Hands-on in Docker deployments for ML workflows on EKS / ECS
• Experience with ML observability (data drift / model drift / performance monitoring / alerting) using CloudWatch / Grafana / Prometheus / OpenSearch.
• Experience with CI / CD / CT using GitHub Actions / Jenkins.
• Experience with JupyterHub/Notebooks, Linux, scripting, and metadata tracking for ML lifecycle.
• Understanding of ML frameworks (TensorFlow / PyTorch) for deployment scenarios.

Job Specific Criteria

• CV Attachment is mandatory
• Please provide CTC Breakup (Fixed + Variable)?
• Are you okay for F2F round?
• Have candidate filled the google form?

Role & Responsibilities

We are looking for a Senior MLOps Engineer with 8+ years of experience building and managing production-grade ML platforms and pipelines. The ideal candidate will have strong expertise across AWS, Airflow/MWAA, Apache Spark, Kubernetes (EKS), and automation of ML lifecycle workflows. You will work closely with data science, data engineering, and platform teams to operationalize and scale ML models in production.

Key Responsibilities:

• Design and manage cloud-native ML platforms supporting training, inference, and model lifecycle automation.
• Build ML/ETL pipelines using Apache Airflow / AWS MWAA and distributed data workflows using Apache Spark (EMR/Glue).
• Containerize and deploy ML workloads using Docker, EKS, ECS/Fargate, and Lambda.
• Develop CI/CT/CD pipelines integrating model validation, automated training, testing, and deployment.
• Implement ML observability: model drift, data drift, performance monitoring, and alerting using CloudWatch, Grafana, Prometheus.
• Ensure data governance, versioning, metadata tracking, reproducibility, and secure data pipelines.
• Collaborate with data scientists to productionize notebooks, experiments, and model deployments.

Ideal Candidate

• 8+ years in MLOps/DevOps with strong ML pipeline experience.
• Strong hands-on experience with AWS:
• Compute/Orchestration: EKS, ECS, EC2, Lambda
• Data: EMR, Glue, S3, Redshift, RDS, Athena, Kinesis
• Workflow: MWAA/Airflow, Step Functions
• Monitoring: CloudWatch, OpenSearch, Grafana
• Strong Python skills and familiarity with ML frameworks (TensorFlow/PyTorch/Scikit-learn).
• Expertise with Docker, Kubernetes, Git, CI/CD tools (GitHub Actions/Jenkins).
• Strong Linux, scripting, and troubleshooting skills.
• Experience enabling reproducible ML environments using Jupyter Hub and containerized development workflows.

Education:

• Master’s degree in computer science, Machine Learning, Data Engineering, or related field.

SAP Basis / HANA 

• Solution Manager/FRUN Experience with detail knowledge of how SOLMAN system is integrated with Ticketing Tools. 
• Experience in Solution Manager Technical monitoring. 
• End to end monitoring for the sap system during the changes when the monitoring is not available or until the new one is in place 
• Manage the team to get the assigned task done on time adhering the SLA. 
• Align with different stakeholders to discuss the progress of multiple tasks. 
• SPOC of Alert management team. 
• Able to solve and coordinate RCA and support during critical system behaviour.
• Audit Experience. 
• Detailed Technical experience in SAP BASIS and HANA systems administrations. 
• Experience in setting up System Replications, High Availability and Disaster recovery. 
• Possess leadership qualities. 
• Proven track record of Client handling. 
• Knowledge of SAP HANA Enterprise Cloud is desirable. 
• Coach others recognize their strengths and encourage them to take ownership of their personal development. 
• Any Experience in SAP tools (SPC, LVM, etc.) will be advantage
• Ready to learn new technologies. 
• Should be ready to work in 24*7 shifts. 
• Any Experience ECS Managed Service Model would be added advantage