At a Glance
- Tasks: Lead the design and development of large-scale data solutions for diverse organisations.
- Company: Join a growing tech consultancy with a focus on innovation and collaboration.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic environment with a strong emphasis on continuous improvement and best practices.
- Why this job: Make a real impact by leading cutting-edge data engineering projects.
- Qualifications: Experience in software engineering and leading teams, with skills in Java, Scala, or Python.
The predicted salary is between 63000 - 77000 £ per year.
An exciting opportunity has arisen for an experienced Lead Data Engineer to join a growing technology consultancy, leading the design and development of large scale, data intensive solutions for major public and private sector organisations.
The successful candidate will combine strong hands on software engineering expertise with technical leadership, taking ownership of complex data engineering components and ensuring solutions are robust, scalable, secure and aligned with business and user requirements.
Working within agile delivery teams, they will lead engineers, establish development standards and drive best practice across the design, development, testing and deployment of modern data platforms.
Key Responsibilities
- Lead the design, development and implementation of data intensive systems, taking ownership of complete components and subsystems from initial design through to coding, testing and defect resolution.
- Remain hands on with software engineering, using open source technologies and commercial data platforms to build scalable data processing and data persistence solutions.
- Establish and enforce software development standards, design patterns and coding practices, coaching engineers to maintain consistency and quality across delivery teams.
- Work closely with solution architects to define and deliver robust ETL and ELT data pipelines, with particular focus on performance, resilience, scalability and non functional requirements.
- Take ownership of unit and integration testing standards, ensuring software quality through effective testing, troubleshooting and performance optimisation.
- Lead technical due diligence and the integration of software products, ensuring solutions meet operational, architectural and security requirements.
- Collaborate with operations teams to ensure applications are deployment ready, maintainable and supported effectively in live environments.
- Work alongside security architects and accreditation teams to ensure data solutions comply with relevant security, regulatory and legal requirements.
- Advise clients, project managers and technical stakeholders on technical approaches, delivery estimates and the implications of user stories and requirements.
- Contribute to technical proposals, solution design and pre sales activities, supporting the development of new client opportunities.
- Lead, manage and develop a small team of engineers, providing technical direction, performance management, mentoring and career development support.
Essential Skills and Experience
- Proven experience leading software engineering teams delivering complex, data intensive systems and components.
- Strong commercial software development experience using at least one of Java, Scala or Python.
- Extensive commercial experience working with Palantir, with the ability to apply the platform within enterprise data engineering solutions.
- Practical experience developing data processing solutions using cloud platforms and technologies such as AWS, Microsoft Azure, Google Cloud Platform or Databricks.
- Expert level SQL skills, including the use of SQL extensions for analytical data processing and engineering.
- Strong understanding of distributed data stores, distributed computing and large scale data processing frameworks.
- Experience establishing and applying software design patterns, coding standards, automated testing and deployment practices.
- Proficient in designing and developing analytical and operational data models.
- Ability to communicate complex technical designs and architectural concepts clearly to both technical and non technical stakeholders.
- Knowledge of data warehousing methodologies, architectures and techniques.
- Relevant AWS, Azure or Google Cloud certifications, particularly within data engineering and data services.
- A passion for continuous improvement, actively contributing to engineering standards and promoting data engineering best practice.
- Experience sharing technical knowledge, contributing to development communities or participating in technology forums.
Lead Data Engineer in London employer: ANSON MCCADE
Anson McCade is an exceptional employer that prioritises employee well-being and professional growth, offering a flexible remote working environment in the UK. With a strong focus on security and digital transformation, employees benefit from comprehensive training programmes and clear pathways for career advancement, all while contributing to impactful projects alongside talented teams and senior stakeholders.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data 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 ANSON MCCADE!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead Data Engineer at ANSON MCCADE.
✨Leverage Professional Networks
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 ANSON MCCADE.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Data Engineer at ANSON MCCADE, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Lead Data 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 ANSON MCCADE, 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 ANSON MCCADE. 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 ANSON MCCADE
✨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 ANSON MCCADE!
✨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.
