At a Glance
- Tasks: Lead teams to create scalable data solutions and engage with stakeholders for impactful projects.
- Company: Dynamic tech company focused on innovative data engineering solutions.
- Benefits: Competitive salary, career growth opportunities, and a collaborative work environment.
- Other info: Join a supportive community that values your growth and development.
- Why this job: Make a real difference in data engineering while leading talented teams and driving innovation.
- Qualifications: Experience in big data technologies and strong programming skills required.
The predicted salary is between 70000 - 80000 £ per year.
Role Overview - SC Cleared or Eligible only
Salary - 70k - 80k per annum
We are seeking an accomplished Lead Data Engineer (SFIA Level 5) to provide technical leadership, direction, and strategy across complex data engineering initiatives.
This role involves leading teams to deliver resilient, scalable, and standards-driven data solutions, while engaging with senior stakeholders to translate requirements into robust data products and services.
The Lead Data Engineer will be responsible for setting engineering standards, embedding best practices, and ensuring delivery aligns with strategic principles.
The role also carries line management responsibilities, helping to build capability within the engineering community.
Key Responsibilities
- Provide technical leadership and set the direction for engineering teams and communities, ensuring delivery adheres to data standards and strategic principles.
- Engage with senior stakeholders to define requirements for complex and sensitive data products, pipelines, and platforms.
- Oversee delivery and user testing of requirements across teams.
- Lead the redevelopment of existing data journeys, enhancing performance, resilience, and scalability, while adapting to evolving systems, tools, and platforms.
- Translate user requirements and data designs into effective, reusable, and standards-compliant data solutions.
- Define, deliver, and embed engineering standards across multiple platforms, keeping them updated and ensuring adherence across teams.
- Champion data validation methods and standards to ensure data quality from source to consumption.
- Standardise code, product, and service quality across engineering teams by implementing best practices and governance.
- Design and promote reusable metadata libraries and cross-business standards in collaboration with other technical disciplines.
- Partner with Lead Data Engineers, Data Architects, and Technologists to design and develop innovative solutions.
- Continually improve data engineering, automation, and scaling capabilities.
- Provide leadership and mentoring, helping to develop the skills and capabilities of the Data Engineer community.
- Carry out line management responsibilities, supporting the growth and development of Data Engineers.
- Ensure alignment and collaboration with teams across Digital Group, Data & Analytics, and Data Practice for consistency and scalability.
Skills & Experience Required
- Proven ability to lead development and delivery of complex data pipelines using big data technologies (Apache Kafka, Spark, or similar) and cloud platforms (AWS, Azure).
- Technical leadership experience, setting team direction and ensuring adherence to data standards and strategic principles.
- Strong programming/coding expertise across Python, SQL, Proc SQL, and cloud technologies (Azure stack, AWS).
- Experience in designing and executing data/code quality assurance processes, troubleshooting, and resolving processing issues.
- Ability to apply standards and tools to design, code, test, correct, and document programs/scripts from agreed specifications.
- Knowledge of data modelling, with experience leading strategies for delivery to wider communities.
- Proven track record leading the development of ETL pipelines for large, complex, or high-volume datasets, with effective delegation and oversight.
Advanced knowledge of data engineering standards, with the ability to establish, maintain, and enforce them across teams.
- Seniority level
- Mid-Senior level
- Employment type
- Full-time
- Job function
- Business Development
Industries: Software Development, IT Services and IT Consulting, and IT System Data Services
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Lead Data Engineer employer: Scrumconnect Consulting
At Scrumconnect Consulting, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to excel in their roles. As a Senior Data Engineer/Architect, you will have access to continuous professional development opportunities and the chance to work on impactful projects within the public sector. Our Staines location offers a vibrant community and convenient access to transport links, making it an ideal place for those seeking a meaningful career in data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer
✨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 Scrumconnect Consulting!
✨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 Scrumconnect Consulting.
✨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 Scrumconnect Consulting.
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When you find a suitable opening like Lead Data Engineer at Scrumconnect Consulting, 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
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 Scrumconnect Consulting, 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 Scrumconnect Consulting. 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 Scrumconnect Consulting
✨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 Scrumconnect Consulting!
✨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.
