At a Glance
- Tasks: Lead the design and implementation of scalable data automation solutions.
- Company: Join a forward-thinking tech company focused on data innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic team environment with exciting projects in data technology.
- Why this job: Make a significant impact by transforming data workflows and driving technical excellence.
- Qualifications: 5+ years in cloud or data engineering with strong leadership skills.
The predicted salary is between 95000 - 95000 £ per year.
Responsibilities
- Architect and lead the implementation of complex data automation solutions that replace manual workflows with scalable, reliable data pipelines across the organization.
- Design and build end‑to‑end Bronze → Silver → Gold transformation pipelines, implementing domain logic, data quality frameworks, and reproducible data products.
- Own the design of the data platform architecture, including ingestion frameworks, transformation patterns, orchestration strategies, and data governance standards.
- Establish and enforce data engineering best practices, including schema evolution, data contracts, validation frameworks, and performance optimization across all data pipelines.
- Build scalable backend data services and APIs that expose curated datasets to analytics tools, product applications, and downstream consumers.
- Lead the integration of data sources from operational systems, external applications, and sensor data, implementing both batch and streaming patterns as needed.
- Partner closely with product teams, data analysts, business stakeholders, and AI Engineers to understand complex data requirements and translate them into robust technical solutions.
- Drive technical excellence by establishing architectural standards, conducting design reviews, and documenting patterns that enable team scalability and maintainability.
- Evaluate and recommend data technologies, tools, and platforms that will improve engineering productivity and data platform capabilities.
Qualifications
- A degree in Computer Science, Mathematics, or a related field.
- 5+ years of experience as a Cloud Engineer, Data Engineer, Backend Engineer, or similar role with demonstrated technical leadership.
- Proven experience architecting and maintaining complex data pipelines, transformation workflows, and data platform components that serve multiple downstream consumers.
- Proven experience building event‑driven and streaming data integrations at scale.
- Expert knowledge of cloud data services across either Azure or AWS ecosystems (e.g., ADLS, ADF, Databricks, Event Hubs, S3, Glue, EMR, Kinesis, Lambda).
- Production experience deploying and managing containerized services in Kubernetes environments (AKS and/or EKS preferred).
- Strong expertise with SQL and NoSQL systems (e.g., Postgres, MongoDB, Redis) including schema design and optimization.
- Knowledge of data governance processes and tools and metadata management solutions.
- Experience with infrastructure as code and platform engineering practices (e.g., Terraform).
- Experience implementing and maintaining CI/CD workflows (Azure Pipelines, GitHub Actions, AWS CodePipeline/CodeBuild, ArgoCD).
- Strong understanding of access control frameworks and security governance in hybrid environments, including integration with enterprise identity providers (e.g., Active Directory/LDAP, SSO, IAM federation).
- Good programming skills in Python.
- Excellent communication and leadership skills, with proven ability to influence technical direction.
Preferred Qualifications
- Strong experience designing and operating data platforms supporting telemetry, sensor, location, and operational technology (OT) data workloads.
- Experience processing and managing large‑scale video, image, and unstructured media datasets, including streaming ingestion and analytics workflows.
- Understanding of feature engineering patterns and data preparation workflows supporting machine learning systems.
- Strong understanding of private cloud and on‑premises environments, including secure service design, network isolation, and hybrid connectivity patterns between on‑prem and public cloud.
- Experience working with maritime, fleet, vessel operations, logistics, or industrial operational domains, including telematics, tracking, asset monitoring, or operational analytics use cases.
Salary
Up to £95,000 per annum.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Cloud Engineer in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Ocean Infinity!
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Ocean Infinity.
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We think you need these skills to ace Senior Cloud Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Ocean Infinity, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Ocean Infinity. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Ocean Infinity
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Ocean Infinity!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
