Infosys

AWS Data Engineer

Job description

Roles and Responsibilities:
  • Work in collaborative teams of Business Analyst and Developers to deliver
  • Plan, Configure, Deploy and Operate a cloud solution
  • Deliver Proof of Concepts for new Solutions on Cloud
  • Leading and delivering high quality, fit for purpose, enterprise aligned technology designs for projects and BAU releases using AWS technologies
  • Establishing positive working relationships with specific business customers, technology stakeholders, vendors and other service providers throughout the SDLC of an assignment /project.
Skill/Competency Requirements:
  • 4+ years’ experience building and supporting large-scale, business critical systems on Public Cloud (AWS Cloud Platform)
  • Data Engineer (elastic data lake) with 4 to 6 years of total IT experience level and with at least 3 year of data design experience in the mix.
  • Redshift, EC2
  • Python, Airflow
  • Tableau
  • Jenkins
  • Advanced SQL, Shell scripting
  • Strong ETL, ELT and data warehousing concepts
  • Informatica BDM {preferred}
  • Snowflake {preferred}
Attitude
  • Collaborative & Persuasive, Self-motivated, Research Oriented, Hands-on, Committed, Always-on learner
  • Working knowledge of AWS Cloud Platform
  • Good understanding of cloud design considerations and limitations and it’s impact on Pricing.
  • Networking principles and protocols such as IP subnetting, routing, firewall rules, Virtual Private Cloud, LoadBalancer, Cloud DNS, Cloud CDN, etc.
  • Proficient in a modern scripting language (preferably Python) for automation of build tasks.
  • Prior experience working with container technology such as Docker, version control systems (Github), build management and CI/CD tools (Concourse, Jenkins), and monitoring tools (App Dynamics, etc.)
  • Experience with infrastructure configuration management tools such as Terraform, Puppet and Chef.
  • Unix/Linux power user
  • Prefer AWS Cloud Certified candidates.
  • Able to demonstrate experience with software engineering practices including CI/CD, Automated testing and Performance Engineering

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