Job Description :
Role: Big Data Engineer/Data Architect
Duration: 5 years funded contract (2 years start initially)

Background check and Drug test prior to joining

Job Description:
The Big Data Engineer/Data Architect will design, build, and provide data analysis and management
guidance and support for:
A diverse set of data environments and management leveraging Google Scientific/Genomics for
handling massive all-by-all comparisons of genomic information for use in application design &
Software-defined network infrastructure technologies focused on security, services operations,
e.g. networking, firewall management, proxy, IT health check management, backup, recovery,
event management, patching, monitoring, etc.
Provides leadership in developing innovative service capabilities for Cloud computing elastic
resources for manipulating enormous datasets in Google Scientific/Genomics capability projects.
Responsible for developing strategies, technology, tools, methods, services and solutions that
position as a recognized leader in providing Big Data services for our Clients.
Design and develop automation to support continuous delivery and continuous integration
processes, analyze client workflows, and determine the best solutions for a successful enterprise
Google Cloud Scientific/Genomics infrastructure.
Work with business stakeholders and senior leaders to deliver on complex, enterprise-level
initiatives that are a part of the company39;s overall strategic direction
Utilize automation tools such as Chef, Jenkins, Git, Electric Flow (Electric Data), or similar tools.
Assist with upgrading, installing, and configuring monitoring solutions for Google Cloud
Scientific/Genomics for Windows and Linux servers.
Manage firewalls, VPNs, and remote access to servers, based on different user roles and access
Work in a DevOps capacity with a desire to automate all repetitive processes within the Google
Cloud Scientific/Genomics environment.
Maintain end-to-end security ensuring best practices are always implemented.
Provision and maintain all servers using configuration management tools, including Chef.
Develop solutions using data services. Research into, and implementation of, new Google Cloud
Scientific/Genomics tools to improve efficiency, performance, and cost-effectiveness.
Working knowledge of supporting IT infrastructure technologies and standards including
software & hardware life cycle, system configuration policies, security, hardening, High
Availability, Disaster Recovery etc.
Monitor and report to management on actual and projected tasks.
Required Experience:
Delivering Infrastructure as Code using Google Cloud.
Using Google Genomics to access Cloud Platform.
Experience securely storing, processing, analyzing, and sharing large, complex data sets
(biological datasets preferred but not required)
Data orchestration and automation tools.
Providing continuous monitoring and support.
Delivering solutions using Agile methodologies.
Experience with automation tools within a Google Cloud environment in production and lower
o Examples: Chef, Jenkins, Git, Electric Flow (Electric Data
Strong practical Linux and Windows based systems administration skills and scripting experience
in Google Cloud/Genomics.

Qualification required:
Experience with the planning, configuration, optimization and deployment of Google Cloud
solutions (e.g., Compute Engine IaaS, PaaS, Google Compute Engine VMs, AD, Automation,
Monitor, Backup/recovery etc.
Required Qualifications:
BS degree in an applicable area (Computer Science, Engineering, MIS, etc
Google Cloud Platform (or Google Scientific/Genomics) Certified
Minimum 2+ years hands-on experience supporting Google Scientific/Genomics cloud
environments, developing and administering an IT operations environment, and administering
servers on Windows or Linux platforms.
Minimum 4+ years39; experience implementing, migrating, managing, and operating
systems/applications in an enterprise data computing environment as well as deploying and
supporting workloads in Google Cloud/Genomics .
Minimum 4+ years39; experience working within a DevOps environment, utilizing Google Cloud
DevOps tools, developing Google Cloud/Genomics solutions, and implementing/improving Google
Genomics Cloud infrastructure processes.