Analytics

Cloud DevOps Engineer

We're looking for engineers who are passionate about subject like information retrieval, distributed computing, artificial intelligence and natural language processing.

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Job Details

  • Design, develop, and deploy highly available, scalable and self-healing Cloud Native Data Solutions using AWS and Azure Cloud Services
  • Design, implement and deploy Continuous Delivery Solutions on AWS, automating Configuration, Provisioning, and Operational Processes 

using AWS Tools and other tools like Ansible and Docker
  • Data ingestion from homogeneous sources, loading data into cloud Blob/Object or SQL Storage
  • Develop batch data processing pipelines using native Spark based Services (AWS Glue, AWS EMR or Azure Databricks).
  • Develop Big Data Warehouse using Cloud SQL Data Warehouse Services (Azure SQL or AWS Redshift)
  • Prototype and implement massive scaled Data Analytics solutions, using cloud big data tools
  • DWH Data Model design, designing tables with indexes and partitioning
  • Create, schedule and execute ETL Workflows, monitoring and management ETL pipelines (Azure Data Factory, AWS Glues and/or AWS Data Pipeline)
  • Provision and deploy Cloud Analytics solutions
  • Operationalize cloud data solutions, implementing Infrastructure as Code, using automated Resource Management templates (AWS CloudFormation, Azure ARM or Azure Python SDK)
  • CI/CD implementation using Azure DevOps tools for automatization of complete development and operations lifecycle using DevOps Tools and Practices
  • Development, management and deployment of Docker Images and containers
  • Automated Provisioning of Cloud resources (VM and Storage Account, SQL DB and Network) using template
  • Provisioning of SQL Data Warehouses (Azure SQL and AWS Redschift), ETL Data Pipelines (Azure Data Factory, AWS Glue pipelines etc.)
  • User account and access management (Azure Active Directory and AWS IAM)
  • Develop Docker Images for batch processing applications and ML Model APIs, using Container Registry and Services for building storing and deploying Docker Images on Cloud
  • Machine Learning on Azure or AWS platform
  • CI/CD implementation using Cloud Native Tools (via Azure Repos, Azure Artifacts, Azure Pipelines and Azure Test Plans)

Basic Qualifications

  • U.S. Citizenship or Residency required
  • MS degree or equivalent in Computer Science or relevant quantitative disciplines like statistics, operations research, bio informatics, mathematics or physics
  • Experience with one or more general purpose programming languages such as Java, C/C++, Python, Scala or R

Preferred Qualifications

  • Basic understanding of Relational and Non-relational Databases
  • Familiarity with Messaging and Queuing Services

    • Experience or Knowledge in the following is an advantage:

  • Experience using AWS or Azure technology
 and hands-on experience programming with AWS or Azure APIs
  • Understanding of automation on AWS or Azure, using deployment tools and/or other Continous-Integration/Configuration-management tools (e.g. Ansible and Terraform)
  • Understanding of Cloud storage options and their underlying consistency models
  • Experience and Knowledge of design of self-healing and fault-tolerant services
  • Experience and Knowledge of techniques and strategies for maintaining high availability

Your prospects at Qimia Inc.

    Awaiting you is a stimulating and challenging work atmospheres,with flat hierarchies and experienced friendly colleagues. Here at Qimia we put a strong focus on the comprehensive training and education of our Engineers and Data Scientists.

    Topics covered in training:

  • AWS Cloud Applications Development:Planning and design of AWS or Azure Data Lakes; Architecture of core AWS or Azure Services like S3, Azure Blob Storage, AWS CloudFormation; Azure Resource Management, Programming with AWS or Azure APIs
  • Continuous Delivery:Application Lifecycle Management (Version Control, Testing, Build-Tools, and Bootstrapping); Infrastructure Configuration and Provisioning Automation; Implementation of CI/CD processes using AWS or Azure Tools/Services; Development and management of scripts and tools to automate operational tasks using the AWS SDKs, CLI, and APIs
  • Security Services:AWS IAM (Identity and Access Management); Azure Active Directory, Implementation and Management of Data Protection; 
 Cloud Security Best Practices
  • Implement Self-Healing application Architectures; Implement project requirement based Front-end, Middle-tier and Data storage Scaling architectures. Implement Fault Tolerance Applications using AWS or Azure Platforms

    • In our practical training, we work intensively with real scenarios/applications and in our theoretical teaching, we cover the topics of AWS or Azure Certification Programs.

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