As Senior DevOps Engineer, you will be a true partner and a member of Testlio’s engineering teams. You will be mainly focusing on DataOps and MLOps tasks to drive data engineering and data science initiatives that are essential part of our multi-region cloud platform. You will create, improve and support data infrastructure and toolings to achieve smooth operations and collaborations between functions and teams.
Why you will love this job?
Make an impact by creating and driving data oriented solutions that enable data products to internal and external users.
Elevate Testlio’s cloud platform and development with new tools and data infrastructure.
Empower users with AI and data solutions to achieve more.
Work within a small team and become a subject matter expert in your respective domain.
Why you will love being a part of Testlio?
A true sense of belonging: the TestLion Pride is a global community of like-minded people who live Testlio’s six values every day. We’re deliberate about building our community with virtual events and activities that keep us connected across the globe.
Growth through learning: knowledge exchange and learning are central to working at Testlio. You’ll find that motivated, experienced TestLions with diverse backgrounds can always introduce you to new perspectives. With unlimited Udemy access and custom-made courses, you've got the perfect environment for both personal and professional development.
Enable human possibilities: your work at Testlio has a larger purpose. As a TestLion you will not only help our customers create well-built digital experiences for their users, but also create opportunities for Testlio's freelance network, and support social impact programs like Ignite.
Freedom to roam: Testlio is a global company that embraces flexibility. You'll have room to work wherever within your region's main time zones. We also want to make sure you can take time off from work to rest. We honor national holidays in your home nation, and provide a generous number of days off, including personal wellness days.
What would your day look like?

• Implementing and managing scalable cloud system configurations and methodologies in AWS.
• Work within the DevOps data engineering team, using your expertise to build highly automated provisioning, monitoring, and operational capabilities for data.
• Support the ongoing growth, design, and expansion of our data platform, including an API layer
• Help find, provision, and support data observability tooling.
• Support Data Engineers in coding and integrating data pipelines for automated deployment.
• Evaluate new tools and approaches to continuously evolve the team’s DataOps practice.
• Ensure key SLAs are managed across a wide range of producers and consumers.
• Build and run essential monitoring infrastructure supporting data pipelines.
• Build and support machine learning initiatives and infrastructure, setups with Sagemaker and/or other (EC, Docker, Kubernetes).
• Bridge the gaps between Dev-Data-ML Ops and build smooth operations.
• Ensure our work respects the rights, regulations, and consent preferences of all stakeholders (PHI/PII, HIPAA, CCPA, GDPR, etc.).
• Create Infrastructure changes via CloudFormation or other similar technologies to practice IaC.
• Keeping systems secure, highly available and scalable. Resiliency is part of the solution.

What do you need to succeed?

• Degree in Computer Science or equivalent experience.
• 5+ years of experience in AWS, Azure or other relative cloud technologies.
• 5+ years experience spanning at least two IT disciplines, including technical architecture, data, application development or operations.
• Excellent interpersonal and communication skills.
• Good knowledge and understanding of the power of CI/CD and the role of SDLC.
• Docker, ECS, Kubernetes... yup, you’ve seen it all or can adopt fast to new technologies
• Understanding Infrastructure-as-Code (IaC) and have practiced it.
• Extensive knowledge with relational databases like PostgreSQL, MariaDB, MySQL or similar.
• Extensive knowledge and experience with Apache Spark, Airflow, Kafka 
• Knowledge of Redshift, Glue and other AWS tools is a strong plus
• Knowledge of secure infrastructure, principles and practices is essential.
• Passion for process automation and keeping things simple
• Self-starter to set goals, metrics and prioritizing tasks to build the future setup
• Full English professional proficiency.