Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Data Governance Engineer

Canonical
Manchester
2 weeks ago
Applications closed

Related Jobs

View all jobs

Lead Data Governance Engineer

Lead Data Engineer

Lead Data Engineer Contract 3-6 months

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Overview

Lead Data Governance Engineer at Canonical. Location: Remote in the EMEA region. The role focuses on data governance policies, processes, standards, and monitoring in compliance with internal policies and applicable regulatory frameworks (e.g., GDPR, DPA, ISO). A successful candidate will develop Python-based tooling to automate the operations of an internal data mesh solution, including data labeling, quality metrics, data access management, and data security best practices.

The Data Governance team in the Commercial Systems unit enables secure and well-governed access to comprehensive data sets from multiple internal and external sources formed into a data mesh. The team uses open-source data governance tools such as Trino and Ranger, defines and executes data governance processes, and democratizes data at Canonical.

Location: This role will be based remotely in the EMEA region.

Responsibilities
  • Define, monitor, and execute data governance policies
  • Design, implement, and maintain tooling for automated data mesh operations
  • Deploy and operate services developed by the team
  • Depending on your seniority, coach, mentor, and offer career development feedback
  • Develop and evangelize engineering and organizational practices
What we are looking for in you
  • 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
  • Track record of going above-and-beyond to achieve outstanding results
  • Experience with data quality, governance, and security processes and tools
  • Experience with software development in Python and SQL
  • Professional written and spoken English with excellent presentation skills
  • Result-oriented, with a personal drive to meet commitments
  • Ability to travel internationally twice a year, for company events up to two weeks long
Nice-to-have skills
  • Performance engineering and security experience
  • Experience with Airbyte, Ranger, Superset, Temporal, or Trino
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 recognize 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 Program
  • Opportunity to travel to new locations to meet colleagues
  • Travel upgrades for long-haul company events
About Canonical

Canonical is a pioneering tech firm at the forefront of open source. As the publisher of Ubuntu, Canonical is a key player in AI, IoT, and cloud software. We recruit on a global basis and hold high standards for new hires. Most colleagues have worked from home since 2004. Working here is a step into the future, challenging you to think differently, work smarter, and learn new skills.

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.

Seniority level
  • Mid-Senior level
Employment type
  • Full-time
Job function
  • Information Technology
  • Industries: Software Development


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.