Big Data Engineer-Release

Job Summary

We are looking for an experienced Release Management Engineer with strong knowledge of release management, Software Development Life Cycle (SDLC), CI/CD techniques, Agile, Scrum, and ITIL processes. The candidate will be responsible for planning, coordinating, and managing software releases across development, testing, staging, and production environments while ensuring release quality, compliance, and minimal business disruption.

Key Responsibilities

• Plan, coordinate, and manage end-to-end release activities across multiple environments.
• Define release schedules, deployment plans, release calendars, and implementation timelines.
• Coordinate with development, QA, DevOps, infrastructure, security, and business teams to ensure successful releases.
• Manage release readiness reviews, approvals, deployment execution, rollback plans, and post-release validation.
• Ensure adherence to SDLC standards, release policies, and change management procedures.
• Understand and support CI/CD pipelines to improve build, testing, deployment, and release automation.
• Work with tools such as Jenkins, Git, GitLab CI/CD, GitHub Actions, Azure DevOps, or similar platforms.
• Facilitate Agile and Scrum practices, including sprint planning, release planning, daily stand-ups, and retrospectives.
• Follow ITIL practices for Change Management, Release Management, Incident Management, and Problem Management.
• Assess release risks, dependencies, and potential impacts before production deployment.
• Track release progress, manage deployment issues, and coordinate incident resolution during release windows.
• Maintain release documentation, deployment checklists, change records, release notes, and audit evidence.
• Conduct post-implementation reviews and identify opportunities for continuous improvement.
• Prepare release status reports, metrics, and stakeholder communications.

We are looking for a Release Management professional with experience in SDLC, CI/CD techniques, Agile/Scrum methodologies, and ITIL processes. The candidate will be responsible for coordinating release activities, managing deployment schedules, ensuring smooth production releases, and collaborating with cross-functional teams to deliver quality software.

Responsibilities

• Plan, coordinate, and manage end-to-end release management activities across environments.
• Prepare release plans, deployment schedules, and release documentation.
• Coordinate with Development, QA, DevOps, and Operations teams to ensure successful releases.
• Monitor and manage CI/CD pipelines and deployment processes.
• Ensure compliance with SDLC standards, ITIL processes, and change management procedures.
• Participate in Scrum ceremonies and Agile delivery activities.
• Identify release risks, dependencies, and issues, and ensure timely resolution.
• Conduct post-release validation and coordinate rollback activities when required.
• Maintain release calendars, status reports, and deployment records.

Required Skills

• Strong knowledge of Release Management and Software Development Life Cycle (SDLC).
• Understanding of CI/CD techniques and deployment processes.
• Experience working with Agile and Scrum methodologies.
• Knowledge of ITIL processes, including Change Management and Incident Management.
• Strong coordination, communication, and stakeholder management skills.
• Experience with release planning, deployment tracking, and risk management.

Company Overview:

Planview is hiring a DevOps Engineer in Bengaluru, India to support Planview SaaS applications across the product line. You will work in a global, collaborative team — owning CI/CD pipelines, cloud infrastructure, and automation to keep deployments fast and systems reliable.

Responsibilities

• Build and maintain CI/CD pipelines in Jenkins for reliable, fast delivery.
• Manage containerized workloads on Docker and ECS — task definitions, services, and clusters.
• Provision and manage AWS infrastructure using Terraform (CloudFormation a plus).
• Automate configuration and deployment tasks using Python (Ansible a plus).
• Set up and maintain monitoring and alerting via New Relic (CloudWatch, Datadog, or Prometheus/Grafana a plus).
• Write Shell and Python scripts to automate operations and reduce manual work.
• Manage Git workflows — branching, merge strategies, and pull request reviews.
• Administer and support MSSQL databases underpinning the product line — backups, restores, and basic performance troubleshooting.
• Troubleshoot deployment, performance, and infrastructure issues with development teams.
• Participate in on-call rotations and drive incident response.
• Continuously improve infrastructure resilience and deployment speed.
• Apply AI-assisted engineering tools (e.g., GitHub Copilot, Claude Code) to speed up IaC authoring, pipeline debugging, and day-to-day scripting.

Qualifications

Must-Have Skills

• Experience: 4–6 years of experience in DevOps, SRE, or Infrastructure Engineering.
• OS: Windows administration (systemd, package management, log analysis).
• Cloud: AWS (Active Directory, ECS, EC2, CloudFront, S3, VPC, IAM, RDS, Lambda basics).
• Source Control: Git — branching, merge/rebase, PR reviews.
• CI/CD (Jenkins): Pipeline creation and basic Groovy scripting.
• Containerization (Docker + ECS): Task definitions, services, and clusters.
• IaC: Terraform.
• Monitoring: New Relic.
• Scripting: Bash and Python scripting for automation.
• Networking Basics: DNS, load balancers, security groups, VPNs.
• Logging: ELK stack / CloudWatch Logs.
• Database: MSSQL administration — backups, restores, basic performance troubleshooting.
• Infrastructure Automation: Hands-on experience automating infrastructure provisioning, configuration, and deployment end-to-end.
• AI-Assisted Engineering: Comfortable working with AI coding/DevOps assistants (e.g., GitHub Copilot, Claude Code) for IaC generation, scripting, and troubleshooting — verified via a mandatory AI proficiency assessment during interviews.

Nice-to-Have Skills

•     Configuration Management: Ansible.

•     Additional IaC: CloudFormation.

•     Architecture: Knowledge of microservices architecture.

•     Cloudflare: DNS, CDN, WAF.

•     Artifact Repositories: Nexus, JFrog Artifactory, ECR.

•     Other CI/CD Tools: GitHub Actions.

•     AWS cost optimization / FinOps awareness.

•     Datadog, CloudWatch, or Prometheus/Grafana.

•     AIOps: Exposure to AI-driven anomaly detection, root-cause analysis, or incident triage (e.g., Dynatrace Davis AI, Datadog Bits AI, Harness AIDA).

•     Database Basics: RDS backups, restores, performance tuning.

IT professional with approximately 4 year experience. Expert in production support, application support, aws, application support devops engineer, linux, docker, github, jenkins, maven, tomcat server, kubernetes.

- 6–7 years of experience operating and enhancing enterprise-scale data platforms.

- Hands-on experience applying DataOps, DevOps, and software engineering practices to data platform operations.

- Professional experience working with AWS cloud environments.

- Experience monitoring, troubleshooting, and remediating issues across data pipelines, orchestration tools, and platform services.

- Working knowledge of data observability concepts and practices.

- Hands-on proficiency with SQL, relational database concepts, and data warehousing.

Role Overview

We are looking for a DevOps / Platform Engineer with 3–4 years of experience to help manage AWS cloud infrastructure, automation, and AI-ready platform operations. You will work closely with engineering and AI teams to ensure scalable, secure, and reliable deployments.

Key Responsibilities

1. AWS & Infrastructure: Manage core AWS services (EC2, EKS, Lambda, RDS, S3, VPC) using Infrastructure-as-Code (Terraform, CloudFormation, or CDK).
2. AI/ML Workflows: Support infra for AI applications, model serving, vector databases, and GPU-based workloads.
3. CI/CD & Automation: Build and maintain deployment pipelines using GitHub Actions, GitLab CI, or Jenkins.
4. Containers & Kubernetes: Deploy and maintain containerized applications using Docker and Kubernetes (EKS) or ECS.
5. Observability & Incident Support: Maintain dashboards and alerts with CloudWatch, Prometheus, or Grafana, and participate in on-call response.
6. Security & FinOps: Apply AWS security best practices (IAM, encryption, secrets) and assist with cloud cost optimization.

Must-Have Skills & Qualifications

1. 3–4 years of experience in DevOps, SRE, or Cloud Infrastructure Engineering.
2. AWS & Containers: Good working knowledge of core AWS services, Docker, and Kubernetes (EKS).
3. Infrastructure-as-Code: Practical experience with Terraform, CloudFormation, or AWS CDK.
4. Linux & Networking: Solid fundamentals in Linux systems, DNS, routing, and load balancing.
5. Scripting: Hands-on scripting proficiency in Python, Bash, or Go.
6. CI/CD & Observability: Experience building CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins) and using monitoring tools (CloudWatch, Prometheus, Grafana, or Datadog).

Nice-to-Have Skills

1. Basic exposure to AI/ML infrastructure, model serving, or GPU-based compute.
2. Experience with event-driven messaging systems (Kafka, Redis, or SQS).
3. Familiarity with GitOps tools and Helm (ArgoCD, Flux, or OpenTelemetry).
4. AWS Certifications (Solutions Architect Associate, SysOps Administrator, or DevOps Engineer).

Overview

Planview has one mission: to build the future of connected work, from ideas to impact.

As the global leader in work and resource management, Planview helps organizations accelerate the achievement of what matters most, supporting our customers from need to speed, from passion to progress, and from overhead to optimization. We provide the industry’s most comprehensive solutions designed for strategic planning, portfolio and resource management, Lean and Agile delivery, product portfolio management, capability, technology management (enterprise architecture), innovation management, collaborative work and project management. Our connected platform of solutions underpins the business and digital transformations of more than 4,500 customers globally, including 59 of the Fortune 100.

At Planview, our people connections drive our innovation and success. Our global team of 1400+ work remotely and across our offices including Austin, Vancouver, Hod HaSharon, Bangalore, and Stockholm. We are proud of our world-class, connected culture built on our shared values, that supports our teams to be successful from anywhere.

The Opportunity

Join our product development team at Planview as a Software Engineer 2 and contribute to the Viz Core Team. This role provides an exciting opportunity to support the development of data processing pipelines and APIs that form the backbone of our software solutions. You will work collaboratively to enhance the efficiency of software delivery, developing solutions that help organizations harness and interpret workflow data.

In this role, you will

•Collaborate with senior engineers to create and refine data processing architectures that integrate with various external tools.

•Assist in analyzing problems, defining requirements, and proposing solutions that align with the team’s objectives.

•Contribute to a culture of quality and continuous improvement by providing thoughtful feedback on code and design.

•Learn and apply best practices in cloud architectures and data processing to deliver high-quality software solutions.

•Engage in an environment that values innovation and teamwork, where your contributions will positively impact the delivery of software solutions.

Who we are looking for

The ideal candidate is an emerging professional in cloud software development with a solid foundation in data processing and software systems. You thrive in collaborative environments and are eager to learn and grow within the field.

Preferred qualifications skills, knowledge, and expertise

•Degree in Computer Science, Engineering, or a related field.

•3+ years of experience with any modern programming language, focusing on back-end systems and cloud-based technologies.

•Basic understanding of data structures, algorithms, and software development methodologies.

•Familiarity with cloud platforms, particularly AWS or similar services.

Other beneficial qualifications

•Exposure to big data technologies like Spark or Apache Kafka.

•Experience with Java (v17), Scala, or other JVM programming languages.

•Familiarity with storage tools such as PostgreSQL and MongoDB.

• Understanding of continuous integration/deployment tooling such as GitHub or Jenkins.

• Awareness of Test-Driven Development practices.

• Basic knowledge of containers and orchestration tools like

Strong Data Engineer (AWS) Profile

2

Mandatory (Experience 1) – Must have minimum 6+ years of experience in Data Engineering, with strong experience designing, developing, and maintaining scalable data pipelines and ETL processes.

3

Mandatory (Experience 2) – Must have 3+ years of hands-on experience with AWS data engineering services, particularly S3, AWS Glue, EMR, Lambda, and Redshift.

4

Mandatory (Experience 3) – Must have strong programming experience in Python, Java, or Scala, with hands-on development of data processing and pipeline solutions.

5

Mandatory (Experience 4) – Must have strong expertise in SQL, data warehousing, and database technologies, including experience with both SQL and NoSQL databases.

6

Mandatory (Experience 5) – Must have hands-on experience working with Big Data technologies and distributed data processing, including designing and optimizing large-scale data pipelines.

7

Mandatory (Experience 6) – Must have experience with data pipeline troubleshooting, monitoring, data quality, governance, and security best practices.

8

Mandatory (Education) – B.Tech / B.E./ M.Tech

Strong Data Engineer (AWS) Profile

2

Mandatory (Experience 1) – Must have minimum 6+ years of experience in Data Engineering, with strong experience designing, developing, and maintaining scalable data pipelines and ETL processes.

3

Mandatory (Experience 2) – Must have 3+ years of hands-on experience with AWS data engineering services, particularly S3, AWS Glue, EMR, Lambda, and Redshift.

4

Mandatory (Experience 3) – Must have strong programming experience in Python, Java, or Scala, with hands-on development of data processing and pipeline solutions.

5

Mandatory (Experience 4) – Must have strong expertise in SQL, data warehousing, and database technologies, including experience with both SQL and NoSQL databases.

6

Mandatory (Experience 5) – Must have hands-on experience working with Big Data technologies and distributed data processing, including designing and optimizing large-scale data pipelines.

7

Mandatory (Experience 6) – Must have experience with data pipeline troubleshooting, monitoring, data quality, governance, and security best practices.

8

Mandatory (Education) – B.Tech / B.E./ M.Tech

• 3 years of relevant experience in DevOps, Site Reliability Engineering (SRE), cloud operations, or application production support.
• Strong practical understanding of AWS cloud services, including compute, storage, IAM, networking, security, and monitoring.
• Good Linux administration skills, including system troubleshooting, performance analysis, log investigation, and service management.
• Hands-on experience with GitLab CI/CD, including pipeline configuration, execution, troubleshooting, YAML files, variables, artifacts, and GitLab Runners.
• Mandatory hands-on experience with Infrastructure as Code (IaC), preferably Terraform, including infrastructure provisioning, configuration management, reusable modules, state management, and troubleshooting deployment issues.
• Working knowledge of Git, branching strategies, merge requests, and version control workflows.
• Good understanding of networking fundamentals, including DNS, TCP/IP, ports, routing, load balancers, and AWS security groups.
• Ability to systematically investigate and resolve infrastructure, application, and deployment issues using logs, metrics, monitoring tools, and dependency analysis.
• Working knowledge of Python or Shell scripting for operational automation and troubleshooting.
• Strong problem-solving skills, communication, collaboration, willingness to learn, and ownership of incidents through resolution.

Preferred Skills and Experience

• Basic SQL knowledge for application and database-related operational investigations.
• Experience with AWS monitoring and logging services, particularly Amazon CloudWatch.
• Familiarity with incident, problem, and change management processes in production environments.
• Exposure to operational automation, proactive monitoring, alert optimization, and root cause analysis (RCA).
• Understanding of cloud infrastructure best practices, including security, reliability, availability, and cost optimization.
• Experience supporting containerized applications using Docker, Kubernetes, or Amazon EKS would be an advantage.