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Our client is supporting companies that have remote call center employees. Their technology is used to increase employee performance.
This is a remote-friendly position!
Design and develop data pipelines, ETL, storage solutions, and workflows that are optimized for speed, fault-tolerance, and scalability
Work with Application, Machine Learning, and Site Reliability/DevOps engineers to create systems that support their varied data needs while allowing for independent manipulation and iteration of data
Define robust data schemas for the rapid intake and processing of customer data with diverse structures
Support product-focused engineering teams with data infrastructure, APIs, and scalable deployments
Architect and author internal libraries for use by fellow engineers
Help create data analytics tools for software telemetry and business intelligence purposes
Cultivate a better understanding of data handling best practices across engineering teams
Collaborate on security efforts for customer data
Who Will Be a Great Fit?
Strong skills with SaaS languages: Should have at least 4 years of experience writing code in one of: Ruby, Go, Python, Scala, Elixir, Java. Should be interested in learning new technologies as well.
Strong understanding of relational and non-relational databases such as PostgreSQL, ElasticSearch, and Redis
Ability to organize and model data to support many use cases
Experience creating and deploying container-based software
Familiarity with asynchronous data processing patterns with an added focus on monitoring and logging
Prior experience working with AWS or a similar cloud provider
A BS/MS in computer science or related field of study, or equivalent experience
Ability to communicate ideas to technical and non-technical colleagues
Please apply to this opening if it sounds like you are a close fit and would make you excited to come to work every day.
Feel free to forward this job opening to qualified individuals!
Integrate new data and big data management technologies and software engineering tools
Utilize the new big data tools
Ensure the data architecture can be extendable for big data solutions
Implement data tools to support analytics and data scientist team
Breathe data systems architecture engineering
Design the data architecture and data integration layers
Ensure that data center networks
Develop business critical data solutions
Manage the migration of data from legacy systems to new data solutions
Troubleshoot data processing and regular data loads
Integrate new data technologies/tools across the enterprise
Evangelize data best practices and implement analytics solutions
Discover data across many different systems, data sources, and data types
Collect and store big data
Executing data center infrastructure engineering projects About AECOM
Executing data center infrastructure engineering projects
Implement data extraction tools with integration of a variety of data sources and data formats
Solve big data problems with smart algorithmic solutions
Assist with data-related technical issues
Build and integrate data from various resources and manage big data