Senior DevOps + Data Engineer

2 days ago

Ahmedabad, Gujarat, India IT Merchant Full time ₹ 8,00,000 - ₹ 24,00,000 per year

Key Responsibilities

DevOps & Infrastructure:

  • Design, implement, and manage CI/CD pipelines for multiple environments.
  • Automate provisioning, deployment, and scaling of infrastructure across AWS, GCP, or Azure.
  • Implement monitoring, alerting, and logging frameworks using tools such as Prometheus, Grafana, ELK Stack, or CloudWatch.
  • Ensure high availability, disaster recovery, and adherence to infrastructure security best practices.
  • Manage containerization and orchestration using Docker, Kubernetes, and Helm.

Data Engineering:

  • Design, build, and optimize data pipelines for batch and real-time processing.
  • Work with ETL frameworks such as Airflow, dbt, or AWS Glue to ensure reliable data flow and transformation.
  • Collaborate with data scientists and analysts to maintain data quality, lineage, and governance.
  • Optimize data storage and retrieval using cloud data warehouses like BigQuery, Redshift, or Snowflake.
  • Integrate diverse data sources and maintain APIs or microservices for data exchange.

Collaboration & Strategy:

  • Partner with development, analytics, and infrastructure teams to improve deployment velocity and system reliability.
  • Define best practices, standards, and guidelines for DevOps and data operations.
  • Mentor junior engineers and promote a culture of automation, reliability, and data excellence.

Required Skills & Experience:

  • 10+ years of experience in DevOps, Infrastructure Automation, or related roles.
  • Proven experience with cloud platforms (AWS, GCP, or Azure).
  • Strong expertise in Infrastructure as Code (IaC) using Terraform, CloudFormation, or Pulumi.
  • Proficiency in scripting and automation using Python, Bash, or Go.
  • Hands-on experience with CI/CD tools (GitHub Actions, Jenkins, GitLab CI, CircleCI, etc.).
  • Experience managing Kubernetes clusters and microservice-based architectures.
  • Strong understanding of data pipelines, ETL tools, and data orchestration frameworks.
  • Familiarity with data modeling, warehousing, and streaming technologies (Kafka, Spark, Flink, etc.).
  • Solid knowledge of monitoring, observability, and security principles.
  • Excellent problem-solving, communication, and leadership abilities.

Good to Have:

  • Experience with machine learning pipelines and MLOps frameworks.
  • Exposure to serverless architectures (AWS Lambda, Google Cloud Functions, etc.).
  • Knowledge of cost optimization and performance tuning in cloud environments.
  • Contributions to open-source projects or technical blogs/publications.

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