Location: Home based - Worldwide
Canonical is a leading provider of open source software and operating systems to the global enterprise and technology markets. Our platform, Ubuntu, is very widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation and IoT. Our customers include the world's leading public cloud and silicon providers, and industry leaders in many sectors. The company is a pioneer of global distributed collaboration, with 1000+ colleagues in 70+ countries and very few roles based in offices. Teams meet two to four times yearly in person, in interesting locations around the world, to align on strategy and execution.
The company is founder led, profitable and growing. We are hiring
Python and Kubernetes Specialist Engineers focused on Data, Workflows, AI/ML and Analytics Solutions
to join our teams building open source solutions for public cloud and private infrastructure.
As a software engineer on the team, you'll collaborate on end-to-end data analytics and MLOps solutions composed of popular, open-source, machine learning tools, such as Kubeflow, MLFlow, DVC, and Feast. You may also work on ETL, data governance and visualization tools like Apache SuperSet, dbt, workflow orchestration tools such as Airflow and Temporal, or data warehouse solutions such as Apache Trino, or ClickHouse. These solutions may be run on servers or on the cloud, on machines or on Kubernetes, on developer desktops, or as web services.
We serve the needs of individuals and community members as much as the needs of our Global 2000 and Fortune 500 customers; we make our primary work available free of charge and our Pro subscriptions are also available to individuals for personal use at no cost. Our goal is to enable more people to enjoy the benefits of open source, regardless of their circumstances.
Location:
This initiative spans many teams that are home-based and in multiple time zones. We believe in distributed collaboration but we also try to ensure that colleagues have company during their work hours! Successful candidates will join a team where most members and your manager are broadly in the same time zone so that you have the benefits of constant collaboration and discussion.
What your day will look like
Develop your understanding of the entire Linux stack, from kernel, networking, and storage, to the application layer
Design, build and maintain solutions that will be deployed on public and private clouds and local workstations
Master distributed systems concepts such as observability, identity, tracing
Work with both Kubernetes and machine-oriented open source applications
Collaborate proactively with a distributed team of engineers, designers and product managers
Debug issues and interact in public with upstream and Ubuntu communities
Generate and discuss ideas, and collaborate on finding good solutions
What we are looking for in you
Professional or academic software delivery using Python
Exceptional academic track record from both high school and university
Undergraduate degree in a technical subject or a compelling narrative about your alternative chosen path
Confidence to respectfully speak up, exchange feedback, and share ideas without hesitation
Track record of going above-and-beyond expectations to achieve outstanding results
Passion for technology evidenced by personal projects and initiatives
The work ethic and confidence to shine alongside motivated colleagues
Professional written and spoken English with excellent presentation skills
Experience with Linux (Debian or Ubuntu preferred)
Excellent interpersonal skills, curiosity, flexibility, and accountability
Appreciative of diversity, polite and effective in a multi-cultural, multi-national organisation
Thoughtfulness and self-motivation
Result-oriented, with a personal drive to meet commitments
Ability to travel twice a year, for company events up to two weeks long
Additional skills that would be nice to have
The following skills may be helpful to you in the role, but we don't expect everyone to bring all of them.
Proven track record of building highly automated machine learning solutions, data pipelines, or orchestrating workflows for the cloud.
Hands-on experience with machine learning libraries, or tools.
Experience with container technologies (Docker, LXD, Kubernetes, etc.)
Experience with public clouds (AWS, Azure, Google Cloud)
Working knowledge of cloud computing
Passionate about software quality and testing
Experience working on an open source project
What we offer colleagues
We consider geographical location, experience, and performance in shaping compensation worldwide. We revisit compensation annually (and more often for graduates and associates) to ensure we recognise outstanding performance. In addition to base pay, we offer a performance-driven annual bonus or commission. We provide all team members with additional benefits, which reflect our values and ideals. We balance our programs to meet local needs and ensure fairness globally.
Distributed work environment with twice-yearly team sprints in person
Personal learning and development budget of USD 2,000 per year
Annual compensation review
Recognition rewards
Annual holiday leave
Maternity and paternity leave
Employee Assistance Programme
Opportunity to travel to new locations to meet colleagues
Priority Pass, and travel upgrades for long haul company events
About Canonical
Canonical is a pioneering tech firm at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and the platform for AI, IoT and the cloud, we are changing the world of software. We recruit on a global basis and set a very high standard for people joining the company. We expect excellence - in order to succeed, we need to be the best at what we do. Most colleagues at Canonical have worked from home since its inception in 2004. Working here is a step into the future, and will challenge you to think differently, work smarter, learn new skills, and raise your game.
Canonical is an equal opportunity employer
We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products.
Whatever your identity, we will give your application fair consideration.
#LI-remote
Location: Limassol
Wisebits — is an international IT holding with a strong technical team!
Our key product is a high-load video hosting platform used by millions of people worldwide every day. With over 15 years on the market, we’ve built a professional team that values engagement and initiative.
If you’re excited about working with a high-load product and want to have an impact on its development, join us!
We are looking for an experienced
Data Analyst
who will help us make key product and business decisions based on data. In this role, you will have the freedom to influence metrics, experiments, and the development of the company’s analytics culture.
What you'll be working on:
Defining and developing key product metrics.
Generating data-driven insights to support product and business decisions.
Designing, launching, and analyzing A/B tests, from hypothesis formulation to final results.
Monitoring key metrics and identifying anomalies or trends.
Writing SQL and Python code to extract, transform, and analyze data.
Participating in the implementation of new tracking events and parameters.
Working closely with product managers, analysts, designers, data scientists, and data engineers.
What we expect from you:
5+ years of experience in analytics.
Deep understanding of A/B experiments and statistics.
Strong knowledge of Python and SQL.
Experience working with ClickHouse and large volumes of data.
Ability to translate business questions into metrics and reports.
Experience with Google Analytics, Amplitude, or similar tools.
Experience with Airflow, preferably together with dbt.
Nice to have:
Experience implementing data governance practices.
Experience using ML approaches in analytics.
Experience managing teams, such as data engineers, data scientists, or product analysts.
What we offer:
No bureaucracy — flexible working conditions.
An extended benefits package, including medical insurance, tax coverage, foreign language courses, professional training, and all necessary work equipment.
Relocation support: we cover relocation expenses for you and your family, including tickets, visa support, and the first month of accommodation.
A friendly international team that values professionalism and collaboration.
Here, you won’t just analyze numbers — you’ll have a real impact on the product and the business.
Work format:
Remote / On-site
Salary:
From €4,000 net per month. The final compensation level may be higher and depends on relevant experience, skills, and overall match with the role requirements.
seniorLimassol; Relocation support: we cover relocation expenses for you and your family, including tickets, visa support, and the first month of accommodation
Location: Limassol
Wisebits — is an international IT holding with a strong technical team!
Our key product is a high-load video hosting platform used by millions of people worldwide every day. With over 15 years on the market, we’ve built a professional team that values engagement and initiative.
If you’re excited about working with a high-load product and want to have an impact on its development, join us!
What you'll be working on:
Participating in the development and improvement of recommendation systems, including user-item, item-item, and cross-platform recommendations.
Optimizing recommendations on category, channel, and tag pages.
Building text-to-video search: embedding models, ranking, and semantic search.
Turning ML prototypes into production services: inference optimization, profiling, feature preparation, and model quality control.
Developing high-load ML services in Python, including gRPC/Triton-based services.
Our stack:
Languages and libraries:
Python, PyTorch, CatBoost, NumPy, Pandas, Polars, CuDF, CuPy.
Infrastructure and deployment:
Kubernetes, Docker, Airflow, Triton Inference Server.
Data storage:
ClickHouse, MySQL.
What we expect from you:
2+ years of experience with recommendation systems, search, or related ML tasks.
Strong knowledge of Python and ML frameworks, such as PyTorch, CatBoost, etc.
Experience deploying models to production.
Understanding of offline and online model evaluation principles.
What we offer:
Work on an ML product used by millions of users, with real product metrics.
A compact team where every engineer has an impact on the product and can develop expertise across several areas.
Experienced colleagues to discuss ideas with, think through solutions together, and launch new projects and features.
A simple structure — minimum bureaucracy, maximum ownership.
Benefits package: medical insurance, tax compensation, professional training, work equipment, and language courses.
Relocation to Cyprus: visa support, relocation coverage, tickets, and the first month of accommodation.
Flexible schedule, a comfortable atmosphere, and team support.
Work format:
Remote / On-site
Salary:
From €4,000 net per month. The final compensation level may be higher and depends on relevant experience, skills, and overall match with the role requirements.
Limassol; Relocation to Cyprus: visa support, relocation coverage, tickets, and the first month of accommodation
Location: Warsaw, PL
We are looking for a Data Engineer to design, develop, and optimize our data infrastructure on Databricks. You will architect scalable pipelines using BigQuery, Google Cloud Storage, Apache Airflow, dbt, Dataflow, and Pub/Sub, ensuring high availability and performance across our ETL/ELT processes. You will leverage Great Expectations to enforce data quality standards. The role also involves building our Data Mart (Data Mach) environment and implementing CI/CD best practices. A successful candidate has extensive knowledge of cloud-native data solutions, strong proficiency with ETL/ELT frameworks (including dbt), and a passion for building robust, cost-effective pipelines.
Responsibilities
Data Architecture & Strategy – Define and implement the overall data architecture on GCP, including data warehousing in BigQuery/Databricks, data lake patterns in Google Cloud Storage, and Data Mart (Data Mach) solutions. Integrate Terraform for Infrastructure as Code to provision and manage cloud resources efficiently. Establish both batch and real-time data processing frameworks to ensure reliability, scalability, and cost efficiency.
Pipeline Development & Orchestration – Design, build, and optimize ETL/ELT pipelines using Apache Airflow for workflow orchestration. Implement dbt (Data Build Tool) transformations to maintain version-controlled data models in BigQuery, ensuring consistency and reliability across the data pipeline. Use Google Dataflow (based on Apache Beam) and Pub/Sub for large-scale streaming/batch data processing and ingestion. Automate job scheduling and data transformations to deliver timely insights for analytics, machine learning, and reporting.
Event-Driven & Microservices Architecture – Implement event-driven or asynchronous data workflows between microservices. Employ
Docker and Kubernetes (K8s)
for containerization and orchestration, enabling flexible and efficient microservices-based data workflows. Implement
CI/CD
pipelines for streamlined development, testing, and deployment of data engineering components.
Data Quality, Governance & Security – Enforce data quality standards using Great Expectations or similar frameworks, defining and validating expectations for critical datasets. Define and uphold metadata management, data lineage, and auditing standards to ensure trustworthy datasets. Implement security best practices, including encryption at rest and in transit, Identity and Access Management (IAM), and compliance with GDPR or CCPA where applicable.
Scientists & Analytics Enablement – Collaborate with Data Science, Analytics, and Product teams to ensure the data infrastructure supports advanced analytics, including machine learning initiatives. Maintain Data Mart (Data Mach) environments that cater to specific business domains, optimizing access and performance for key stakeholders.
Requirements
1. Experience
– 3+ years of professional experience in data engineering, with at least 1 year
in mobile data
2. Technical Expertise with GCP Stack
– Proven track record building and maintaining BigQuery environments and
Google Cloud Storage based data lakes.
– Deep knowledge of Apache Airflow for scheduling/orchestration and ETL/ELT
design.
– Experience implementing dbt for data transformations, RabbitMQ for
event-driven workflows, and Pub/Sub + Dataflow for streaming/batch data
pipelines.
– Familiarity with designing and implementing Data Mart (Data Mach) solutions,
as well as using Terraform for IaC.
3. Programming & Containerization
– Strong coding capabilities in Python, Java, or Scala, plus scripting for
automation.
– Experience with Docker and Kubernetes (K8s) for containerizing data-related
services.
– Hands-on with CI/CD pipelines and DevOps tools (e.g., Terraform, Ansible,
Jenkins, GitLab CI) to manage infrastructure and deployments.
4. Data Quality & Governance
– Proficiency in Great Expectations (or similar) to define and enforce data quality standards.
– Expertise in designing systems for data lineage, metadata management, and
compliance (GDPR, CCPA).
– Strong understanding of OLTP (Online Transaction Processing) and OLAP
(Online Analytical Processing) systems.
5. Communication
– Excellent communication skills for both technical and non-technical
audiences.
– High level of organization, self-motivation, and problem-solving aptitude.
What we offer
Competitive compensation based on your experience and expertise
Long-term contract-based collaboration
A collaborative and open environment
Flexible collaboration arrangements
УдалённоThis initiative spans many teams that are home-based and in multiple time zones; Successful candidates will join a team where most members and your manager are broadly in the same time zone so that you have the benefits of constant collaboration and discussion
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