We're Hiring: DevOps Engineer | Data Platform
Eazyway is hiring on behalf of DataPMI (datapmi.com). We are seeking a skilled DevOps Engineer to support and automate our data platform ecosystems. The ideal candidate will have a strong focus on CI/CD for modern data stacks, particularly around Databricks, dbt, Airflow, and Azure DevOps. You will be responsible for building, deploying, and managing scalable, reliable, and automated data engineering pipelines.
Location: Bangalore
Total Positions: 1
Experience: 3+ years
Work Type: Full-time | On-site
Primary Skills (Mandatory)
- CI/CD in Databricks & dbt – Design and implement automated CI/CD workflows for Databricks notebooks, jobs, and dbt models (e.g., using dbt Cloud or dbt Core with Databricks).
- Apache Airflow – Manage and deploy DAGs; integrate Airflow with Databricks operators; handle environment and dependency management.
- Azure DevOps YAML Pipelines – Build and maintain multi-stage YAML pipelines for CI/CD, including variable groups, service connections, and approvals.
- Databricks Asset Bundles (DABs) – Use DABs to define, deploy, and manage Databricks resources (jobs, notebooks, models, etc.) as code.
Additional DevOps Skills (Nice to Have / Growing Need)
Infrastructure as Code
- Terraform – Provision Azure resources (Databricks workspaces, ADLS, Key Vaults, VNets, Airflow environments).
CI/CD & Automation
- GitHub Actions or GitLab CI
- dbt CI/CD – Integration with dbt Cloud or dbt Core + GitHub + Databricks
- Unit & integration testing in CI pipelines (e.g., pytest for Databricks notebooks, dbt tests)
Containerization & Orchestration
- Docker: Containerising Airflow workers, dbt execution environments, or custom Databricks Python wheels
- Kubernetes (AKS): Running Airflow or custom data apps (helpful but not mandatory)
Monitoring & Observability
- Azure Monitor, Log Analytics Workspaces
- Prometheus + Grafana (if Airflow runs on K8S)
- Databricks Jobs & Cluster monitoring, alerting on pipeline failures
Security & Compliance
- Azure Key Vault for secrets management
- Service Principals, Managed Identities, RBAC for Databricks & Airflow
Version Control & Collaboration
- Git (GitHub / Azure Repos) – Branch strategies (GitFlow / trunk-based) for data code
Key Responsibilities
Build & Maintain CI/CD Pipelines
- Automate deployment of Databricks jobs, notebooks, libraries, and dbt models.
- Use Azure DevOps YAML pipelines to promote code across dev test prod.
Manage Databricks Environments
- Implement Databricks Asset Bundles for repeatable, versioned deployments.
- Control cluster policies, secrets, and job schedules as code.
Operationalize Airflow
- Deploy, upgrade, and scale Airflow (e.g., on AKS or Azure Container Instances).
- Automate DAG deployment via Git + CI/CD.
Collaborate with Data Engineers
- Enable dbt + Databricks workflows with proper CI (e.g., dbt build --select state: modified).
- Troubleshoot pipeline failures, performance issues, and dependency conflicts.
Implement IaC & Environment Consistency
- Use Terraform to spin up and tear down ephemeral environments for testing.
Required Qualifications
- 3+ years of DevOps experience with a focus on data/analytics platforms
- Strong hands-on experience with Azure DevOps YAML pipelines
- Strong experience with Databricks and dbt (Core or Cloud)
- Working knowledge of Apache Airflow (deployment, not just authoring)
- Experience with Databricks Asset Bundles
- Proficiency in Python
Preferred Qualifications
- Databricks Certified: Data Engineer or Platform Admin
- Azure DevOps Certification
- Experience with dbt Cloud APIs and CI jobs
- Exposure to Delta Lake, Spark tuning, or Unity Catalog
Job Code: EZW-100125
Only 1 Vacancy | Attractive Salary
How to Apply
Step 1: Register as a Job Seeker using the link below:
https://eazyway.io/job-seeker/register
Step 2: Log in after completing the registration
Step 3: Search using Job Code: EZW-100125 (Recruitment Job Section)
Step 4: Submit your application
Apply Here:https://eazyway.io/job-seeker/register
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