Engineering Manager (Engineering Leader Cloud Infrastucture)

Job Title : Senior DevOps Engineer

Experience : 5+ Years

Location : Gurgaon, Sector 39

About the Role :

We are seeking an experienced Senior DevOps Engineer to lead our DevOps practices, manage a small team, and build functional, scalable systems that enhance customer experience. You will be responsible for deployments, automation, troubleshooting, integrations, monitoring, and team mentoring while ensuring secure and efficient operations.

Mandatory Skills :

Linux Administration, Shell Scripting, CI/CD (Jenkins), Git/GitHub, Docker, Kubernetes, AWS, Ansible, Database Administration (MariaDB/MySQL/MongoDB), Apache httpd/Tomcat, HAProxy, Nagios, Keepalived, Monitoring/Logging/Alerting, and On-premise Server Management.

Key Responsibilities :

• Implement and manage integrations as per business and customer needs.
• Deploy product updates, fixes, and enhancements.
• Provide Level 2 technical support and resolve production issues.
• Build tools to reduce errors and improve system performance.
• Develop scripts and automation for CI/CD, monitoring, and visualization.
• Perform root cause analysis of incidents and implement long-term fixes.
• Ensure robust monitoring, logging, and alerting systems are in place.
• Manage on-premise servers and ensure smooth deployments.
• Collaborate with development teams for system integration.
• Mentor and guide a team of 3 to 4 engineers.

Required Qualifications & Experience :

• Bachelor’s degree in Computer Science, Software Engineering, IT, or related field (Master’s preferred).
• 5+ years of experience in DevOps engineering with team management exposure.
• Strong expertise in:
• Linux Administration & Shell Scripting
• CI/CD pipelines (Jenkins or similar)
• Git/GitHub, branching, and code repository standards
• Docker, Kubernetes, AWS, Ansible
• Database administration (MariaDB, MySQL, MongoDB)
• Web servers (Apache httpd, Apache Tomcat)
• Networking & Load Balancing tools (HAProxy, Keepalived)
• Monitoring & alerting tools (Nagios, logging frameworks)
• On-premise server management
• Strong debugging, automation, and system troubleshooting skills.
• Knowledge of security best practices including data encryption.

Personal Attributes :

• Excellent problem-solving and analytical skills.
• Strong communication and leadership abilities.
• Detail-oriented with a focus on reliability and performance.
• Ability to mentor juniors and collaborate with cross-functional teams.
• Keen interest in emerging DevOps and cloud trends.

• Experience with Infrastructure-as-Code tools(IaS) like Terraform and Cloud Formation.
• Proficiency in cloud-native technologies and architectures (Docker/ Kubernetes), Ci/CD pipelines.
• Good experience in Javascript.
• Expertise in Linux / Windows environment.
• Good Experience in Scripting languages like PowerShell / Bash/ Python.
• Proficiency in revision control and DevOps best practices like Git

Role: Full-Time, Long-Term Required: Docker, GCP, CI/CD Preferred: Experience with ML pipelines

OVERVIEW

We are seeking a DevOps engineer to join as a core member of our technical team. This is a long-term position for someone who wants to own infrastructure and deployment for a production machine learning system. You will ensure our prediction pipeline runs reliably, deploys smoothly, and scales as needed.

The ideal candidate thinks about failure modes obsessively, automates everything possible, and builds systems that run without constant attention.

CORE TECHNICAL REQUIREMENTS

Docker (Required): Deep experience with containerization. Efficient Dockerfiles, layer caching, multi-stage builds, debugging container issues. Experience with Docker Compose for local development.

Google Cloud Platform (Required): Strong GCP experience: Cloud Run for serverless containers, Compute Engine for VMs, Artifact Registry for images, Cloud Storage, IAM. You can navigate the console but prefer scripting everything.

CI/CD (Required): Build and maintain deployment pipelines. GitHub Actions required. You automate testing, building, pushing, and deploying. You understand the difference between continuous integration and continuous deployment.

Linux Administration (Required): Comfortable on the command line. SSH, diagnose problems, manage services, read logs, fix things. Bash scripting is second nature.

PostgreSQL (Required): Database administration basics—backups, monitoring, connection management, basic performance tuning. Not a DBA, but comfortable keeping a production database healthy.

Infrastructure as Code (Preferred): Terraform, Pulumi, or similar. Infrastructure should be versioned, reviewed, and reproducible—not clicked together in a console.

WHAT YOU WILL OWN

Deployment Pipeline: Maintaining and improving deployment scripts and CI/CD workflows. Code moves from commit to production reliably with appropriate testing gates.

Cloud Run Services: Managing deployments for model fitting, data cleansing, and signal discovery services. Monitor health, optimize cold starts, handle scaling.

VM Infrastructure: PostgreSQL and Streamlit on GCP VMs. Instance management, updates, backups, security.

Container Registry: Managing images in GitHub Container Registry and Google Artifact Registry. Cleanup policies, versioning, access control.

Monitoring and Alerting: Building observability. Logging, metrics, health checks, alerting. Know when things break before users tell us.

Environment Management: Configuration across local and production. Secrets management. Environment parity where it matters.

WHAT SUCCESS LOOKS LIKE

Deployments are boring—no drama, no surprises. Systems recover automatically from transient failures. Engineers deploy with confidence. Infrastructure changes are versioned and reproducible. Costs are reasonable and resources scale appropriately.

ENGINEERING STANDARDS

Automation First: If you do something twice, automate it. Manual processes are bugs waiting to happen.

Documentation: Runbooks, architecture diagrams, deployment guides. The next person can understand and operate the system.

Security Mindset: Secrets never in code. Least-privilege access. You think about attack surfaces.

Reliability Focus: Design for failure. Backups are tested. Recovery procedures exist and work.

CURRENT ENVIRONMENT

GCP (Cloud Run, Compute Engine, Artifact Registry, Cloud Storage), Docker, Docker Compose, GitHub Actions, PostgreSQL 16, Bash deployment scripts with Python wrapper.

WHAT WE ARE LOOKING FOR

Ownership Mentality: You see a problem, you fix it. You do not wait for assignment.

Calm Under Pressure: When production breaks, you diagnose methodically.

Communication: You explain infrastructure decisions to non-infrastructure people. You document what you build.

Long-Term Thinking: You build systems maintained for years, not quick fixes creating tech debt.

EDUCATION

University degree in Computer Science, Engineering, or related field preferred. Equivalent demonstrated expertise also considered.

TO APPLY

Include: (1) CV/resume, (2) Brief description of infrastructure you built or maintained, (3) Links to relevant work if available, (4) Availability and timezone.

Acceldata is creating the Data observability space. We make it possible for data-driven enterprises to effectively monitor, discover, and validate Data platforms at Petabyte scale. Our customers are Fortune 500 companies including Asia's largest telecom company, a unicorn fintech startup of India, and many more. We are lean, hungry, customer-obsessed, and growing fast. Our Solutions team values productivity, integrity, and pragmatism. We provide a flexible, remote-friendly work environment.

We are building software that can provide insights into companies' data operations and allows them to focus on delivering data reliably with speed and effectiveness. Join us in building an industry-leading data observability platform that focuses on ensuring data reliability from every spectrum (compute, data and pipeline) of a cloud or on-premise data platform.

Position Summary-

This role will support the customer implementation of a data quality and reliability product. The candidate is expected to install the product in the client environment, manage proof of concepts with prospects, and become a product expert and troubleshoot post installation, production issues. The role will have significant interaction with the client data engineering team and the candidate is expected to have good communication skills.

Required experience

1. 6-7 years experience providing engineering support to data domain/pipelines/data engineers.
2. Experience in troubleshooting data issues, analyzing end to end data pipelines and in working with users in resolving issues
3. Experience setting up enterprise security solutions including setting up active directories, firewalls, SSL certificates, Kerberos KDC servers, etc.
4. Basic understanding of SQL
5. Experience working with technologies like S3, Kubernetes experience preferred.
6. Databricks/Hadoop/Kafka experience preferred but not required

Experienced with Azure DevOps, CI/CD and Jenkins.

Experience is needed in Kubernetes (AKS), Ansible, Terraform, Docker.

Good understanding in Azure Networking, Azure Application Gateway, and other Azure components.

Experienced Azure DevOps Engineer ready for a Senior role or already at a Senior level.

Demonstrable experience with the following technologies:

Microsoft Azure Platform As A Service (PaaS) product such as Azure SQL, AppServices, Logic Apps, Functions and other Serverless services.

Understanding of Microsoft Identity and Access Management products such including Azure AD or AD B2C.

Microsoft Azure Operational and Monitoring tools, including Azure Monitor, App Insights and Log Analytics.

Knowledge of PowerShell, GitHub, ARM templates, version controls/hotfix strategy and deployment automation.

Ability and desire to quickly pick up new technologies, languages, and tools

Excellent communication skills and Good team player.

Passionate about code quality and best practices is an absolute must

Must show evidence of your passion for technology and continuous learning

• Experience working in advanced iterative methodologies such as Agile and Safe.
• Experience with containers and orchestration (Docker, Kubernetes).
• Comfortable working in complex and demanding environments with high degree of change.
• Ability to view system perspective and to perform thorough investigations.
• Experience in frequent delivery to production.
• Microservice-based architecture (Jenkins, Docker, CI/CD, ELK)
• Experience with modern software components (Mongo, Elasticsearch, Kafka).
• Expertise in software development methodologies.
• Understanding of protocols/technologies like HTTP, SSL, LDAP, SSH, SAML, etc.
• Possession of a deep knowledge of development workflows with Git.
• Experience with MySQL or another relational database Environment.
• Automation testing (component, integration and end2end)

We are looking for a full-time remote DevOps Engineer who has worked with CI/CD automation, big data pipelines and Cloud Infrastructure, to solve complex technical challenges at scale that will reshape the healthcare industry for generations. You will get the opportunity to be involved in the latest tech in big data engineering, novel machine learning pipelines and highly scalable backend development. The successful candidates will be working in a team of highly skilled and experienced developers, data scientists and CTO.

Job Requirements

• Experience deploying, automating, maintaining, and improving complex services and pipelines • Strong understanding of DevOps tools/process/methodologies
• Experience with AWS Cloud Formation and AWS CLI is essential
• The ability to work to project deadlines efficiently and with minimum guidance
• A positive attitude and enjoys working within a global distributed team

Skills

• Highly proficient working with CI/CD and automating infrastructure provisioning
• Deep understanding of AWS Cloud platform and hands on experience setting up and maintaining with large scale implementations
• Experience with JavaScript/TypeScript, Node, Python and Bash/Shell Scripting
• Hands on experience with Docker and container orchestration
• Experience setting up and maintaining big data pipelines, Serverless stacks and containers infrastructure
• An interest in healthcare and medical sectors
• Technical degree with 4 plus years’ infrastructure and automation experience