About the job
The AgyleTime (Playvox WFM) team continues to grow globally, as part of that growth we are
looking for a passionate Data Engineer. This is a key role in our continued focus in data and machine
learning to build world leading solutions in WFM. The successful candidate will be involved in the
design, creation, and maintenance of a scalable platform for training, deploying, and monitoring our
The ideal person is someone that is keen to get involved in a small, and fast paced team
environment. You will work closely with our talented team of Engineers and with data science
functions to build real-time solutions. You have the experience but want to apply that knowledge to
build something new and use the latest offerings from AWS. Success is measured by enabling our
ML and Feature teams to build scalable, reliable, and easy-to-use machine learning workflows that
underpin the customer experience.
You will be empowered to show your innovative thinking both at the application and infrastructure
level, making this a challenging and dynamic job. We’re looking for someone who is a proactive
thinker who loves to solve problems. Someone who takes accountability, builds trust and easily
networks with people of all backgrounds. This role can be located in Sydney or elsewhere in
Australia for the right applicant.
We encourage you to apply even if you may not meet every requirement in this posting. We value
diversity and our environment is supportive, challenging and focused on the consistent delivery of
high quality, meaningful work.
As an AWS Data Engineer, you will:
● You will partner with ML engineers, data scientists/engineers, and product engineering
teams to understand business needs, find the right solution to a problem, and ship products.
● You will apply your system software and collaborate with BI and ML engineers to build
scalable, reliable, and easy-to-use machine learning workflows and deploy in live
● You will architect, create, and maintain real-time data streaming from numerous sources for
training, deploying, and monitoring ML models, microservices, and APIs in AWS
● You will work closely with other teams to ensure that applications that require ML services
● You will identify technical requirements and deliver solutions within a distributed team.
● You will automate various steps in ML workflow, from model training, inference, and
We are looking for experience in the following skills and qualifications:
● BS/MS degree in Software Engineering, Computer Science, Information Technology
discipline or a related field.
● Minimum of 3+ years of hands-on experience as Data Engineer or similar positions in
engineering or implementing solutions on AWS. ( Instead of a degree, minimum of five years
related work experience)
● Strong hands-on design and development background using AWS to build data-intensive
infrastructure, specially for machine learning applications
● Hands-on background working with AWS (EC2, S3, Athena, SQS, Lambda, ECS) and
● Strong AWS experience with (AWS Lake Formation, S3, Glue, Athena, Kinesis, RDS)
● Proven experience working with database in using low latency data management systems
such as Redis and DynamoDB
● Solid knowledge of SQL, databases, data warehousing, ETL and other data tools
● Proven experience with Data Lake concepts and relational database concepts
● Experience building and maintaining real-time data streaming from numerous sources for
low-latency data processing
● Proficient in Python. Solid experience writing and maintaining high-quality production code in
Python and other scripting languages
● Hands on experience with development resources; GitHub, containerization and deployment
● Knowledge of data connection & import, data preparation & transformation, data gateway &
warehousing, for business intelligence projects
● Experience with systems engineering and software development using continuous
integration and delivery.
● Experience with distributed systems and microservice architecture
The following skills will be considered a plus:
● Python, CI/CD - automation
● Experience with data visualization tools (datadog)
● Experience with Docker, Kubernetes or similar orchestration and configuration management
● Knowledge of IAM Roles and Security Groups within AWS
● Experience with building APIs (Flask)
● Familiarity working with Data Science teams and productionizing machine learning models
● Good documentation and communication skills
About Agyle Time
Agyle Time was founded in 2014 by a dedicated team with a common goal: to create a solution that
fills a gap in the workforce management industry. Agyle Time provides workforce management
capabilities in a single, specialized Software-as-a-Service platform including forecasting, scheduling,
real time monitoring and analytics and reporting. The AgyleTime product is fully cloud based,
developed as a series of micro-services and leveraging the AWS infrastructure and ecosystem.
We understand the day-to-day challenges in workforce management, and how to best help overcome
those challenges using technology. Our mission is to create software for our customers that is
feature-rich and simple to use, making our customers’ lives easier.
In January 2021, Agyle Time merged with Playvox, to bring a full Workforce Engagement
Management to customer service organisations. Our customers span industries across financial
services, government, retail, technology, and utilities. We support customers with contact center
operations throughout Asia Pacific, the USA and Europe. They range in size from approximately 50
seats to approximately 1000, and the rapid uptake and growth means that we are looking for great
people to join us; we are a small but fast-evolving team who pull together to produce and deliver
amazing client outcomes. We are looking for a like-minded person to join our dynamic team.