Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join our team to build and optimise data platforms using cutting-edge technologies.
- Company: Dataiku, a leader in AI success and enterprise analytics.
- Benefits: Competitive salary, remote work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on continuous learning and diversity.
- Why this job: Make a real impact by delivering data solutions that drive innovation across the company.
- Qualifications: 3+ years in Data Engineering, expertise in SQL & Python, and strong problem-solving skills.
The predicted salary is between 50000 - 65000 £ per year.
Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require. Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack—empowering organizations to run AI across multi‑vendor environments with centralized governance.
Dataiku is looking for a Data Engineer II to join our Enterprise Data and Analytics (EDA) team. As a member of the EDA Team, you will play a central role in delivering data to fuel analytics, AI, and data‑driven insights to various stakeholders and teams within the company. You will also be a key technical member contributing to the Data Platform that fuels centralized analytics, Generative AI engineering, embedded analytics teams, and self‑service users across the organization.
You will become a technical expert on the platforms we work in and help drive engineering excellence both within the EDA team and across the wider Analytics Community. The Data Engineering day‑to‑day will primarily be within the Data Platform built using Snowflake, Dataiku, and GitHub. Primary development will focus on Python & SQL, DataOps processes built within GitHub Actions & Dataiku, and data platform processes built within Snowflake & Dataiku.
Non‑technical skills and learning are also critical, as you will collaborate with engineers from various teams and help deliver solutions across a wide variety of technical domains. Strong software development lifecycle knowledge and DataOps skills are a must. The ideal candidate is naturally curious, has excellent verbal and written communication skills, a sharp analytical mind, a positive attitude towards work, and thrives when collaborating towards a shared goal. This is an internal and non‑client‑facing role.
What You’ll Do
Dataiku is unique in that every Dataiker is encouraged to use our own product within our Enterprise Data Platform. That means this is a unique opportunity to deliver a scalable platform with governed data to fuel an entire company of current or potential Data Analysts! Your responsibilities within the team include:
- Be an expert level engineer within the Dataiku Platform including Platform Automation, GenAI Capabilities, Plugin Development, maintenance & troubleshooting
- Be an expert level engineer within Snowflake for data engineering and security/governance features
- Build & maintain python & SQL based platform automation process
- Build & maintain data quality metrics & observability to help drive data quality standards
- Design data models for both short term and long term use cases to support data warehouse scalability
- Build & maintain administration systems and applications for monitoring, alerting, data observability, access management, platform metrics, and end user transparency
- Build & maintain GenAI Platform solutions focused on security and governance for engineering delivery
- Build & maintain DataOps process for SDLC delivery
- Identify opportunities for improvements & optimization for greater scalability & delivery velocity
- Collaborate closely with Analytics Engineers to provide data & data models for analytical deliverables
- Perform root cause analysis on often complex errors to help ensure data pipeline availability
- Help drive technical & architectural decisions on the data platform including decisions on data architecture, data engineering processes, data quality frameworks, data access security & governance frameworks, DataOps processes & data consumption models
- Help test new features in Dataiku and partner tools to both provide feedback internally as well as determine value towards internal analytics & data platform integration
- Work closely with key stakeholders across the organization including Infra, embedded analytics teams, Product and Engineering to help foster both technical implementations & requirements gathering
- Proactively drive innovation internally with dedicated innovation time & projects that aim to be transformational for either the platform, team or company as a whole
- Actively contribute to the expertise level and competencies of the EDA Team and participate in the creation and support of data development standards and best practices
Requirements
- 3+ years of relevant experience in Data Engineering / Data Platform Engineering
- Expertise in SQL & Python is a must. Experience in Dataiku DSS is a big plus
- Prior experience with Snowflake strongly desired
- Prior experience with DevOps technologies such as Github Actions, Azure DevOps or Jenkins
- Strong understanding of data architecture & data modeling concepts
- Prior experience building and maintaining replication & data pipelines in a cloud data warehouse or data lake environment
- Excellent analytical and creative problem‑solving skills – exhibit confidence to ask questions to bring clarity, share ideas and challenge the norm
- Passion for continuous learning and teaching to help learn & teach new technologies & implementation strategies
- Experience working with complex stakeholders; dissecting vague asks and helping to define tangible requirements
- Ability to manage multiple projects and time constraints simultaneously in a high trust remote environment
- Ability to wear multiple hats depending on the project with the focus on accomplishing end goals while inspiring colleagues to do the same
- Excellent written and verbal communication skills (especially with senior level stakeholders) with the ability to speak to both the business value, data products, & technical capabilities of a platform. Ability to create clear and concise documentations with a high degree of precision
Our practices are rooted in the idea that everyone should be treated with dignity, decency and fairness. Dataiku also believes that a diverse identity is a source of strength and allows us to optimize across the many dimensions that are needed for our success. Therefore, we are proud to be an equal opportunity employer. All employment practices are based on business needs, without regard to race, ethnicity, gender identity or expression, sexual orientation, religion, age, neurodiversity, disability status, citizenship, veteran status or any other aspect which makes an individual unique or protected by laws and regulations in the locations where we operate. This applies to all policies and procedures related to recruitment and hiring, compensation, benefits, performance, promotion and termination and all other conditions and terms of employment. If you need assistance or an accommodation, please contact us.
Data Engineer II in London employer: Dataiku
Contact Detail:
Dataiku Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer II in London
✨Tip Number 1
Get to know the company inside out! Research Dataiku's products and values, and think about how your skills as a Data Engineer II can contribute to their mission. This will help you stand out in interviews.
✨Tip Number 2
Network like a pro! Connect with current Dataiku employees on LinkedIn or attend industry events. Building relationships can give you insider info and might even lead to a referral!
✨Tip Number 3
Show off your skills! If you have a portfolio of projects or contributions to open-source, make sure to highlight them. Demonstrating your expertise in Python, SQL, and DataOps can really impress the hiring team.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the Dataiku team.
We think you need these skills to ace Data Engineer II in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your expertise in SQL and Python right from the get-go. We want to see how your skills align with what we're looking for, so don’t hold back on showcasing your experience with Dataiku and Snowflake!
Tailor Your Application: Take a moment to customise your application for the Data Engineer II role. Mention specific projects or experiences that relate to data engineering and how you’ve tackled challenges in the past. This helps us see how you fit into our team!
Be Clear and Concise: When writing your application, clarity is key! Use straightforward language and avoid jargon where possible. We appreciate well-structured applications that are easy to read and understand, especially when it comes to your technical capabilities.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Dataiku
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially SQL, Python, and Dataiku. Brush up on your knowledge of Snowflake and GitHub Actions too, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex data engineering challenges. Highlight your analytical skills and how you approached problem-solving, as this role requires a sharp mind and creativity.
✨Communicate Clearly
Since this role involves collaboration with various teams, practice articulating your thoughts clearly. Be ready to explain technical concepts in simple terms, especially when discussing data models or engineering processes with non-technical stakeholders.
✨Demonstrate Your Curiosity
Express your passion for continuous learning and innovation. Share any recent projects or technologies you’ve explored that relate to data engineering or AI, as this shows you're proactive and eager to contribute to the team’s success.