At a Glance
- Tasks: Lead end-to-end delivery of data engineering projects on Azure Fabric.
- Company: Dynamic tech company focused on innovative data solutions.
- Benefits: Competitive salary, flexible work options, and leadership development opportunities.
- Other info: Join a collaborative environment with exciting career growth potential.
- Why this job: Shape the future of data engineering while leading a talented team.
- Qualifications: 10+ years in data engineering with strong leadership skills.
The predicted salary is between 60000 - 75000 £ per year.
Role Overview
The end‑to‑end delivery of Database Replication (Hydration) initiatives on Azure Fabric / One Lake.
This role blends strong data background with delivery ownership, team leadership, and stakeholder management.
Key Responsibilities
- Own end-to-end delivery of assigned modules from Development through Release, based on approved Solution Architecture Designs
- Lead and coordinate Development, Dev Ops, QA, Architecture, and Release Engineering teams to ensure seamless delivery.
- Be accountable for delivery timelines, quality, risks, and outcomes, ensuring alignment with programme objectives and commercialization timelines.
- Provide technical direction while managing priorities, inter-team dependencies, and delivery sequencing.
- Act as the single point of contact for assigned teams and the single point of accountability for escalations.
- Proactively identify, track, and mitigate delivery and technical risks, maintaining visibility through structured reporting and RAID management.
- Mentor teams on data engineering, database replication, and delivery best practices to improve overall execution quality.
- Communicate delivery progress, risks, and issues clearly to senior stakeholders.
Required Skills & Experience
- Minimum 10+ years of experience managing Data Engineering programs
- Strong background in data warehousing, Azure, and Dev Ops practices
- Strong understanding of database replication and Change Data Capture (CDC)
- Strong Experince with Oracle Golden Gate (OGG), SQL Server, Azure data services (fundamentals), Dev Ops practices, and networking to guide delivery decisions and resolve issues.
- Working knowledge of Azure Data Services, including Microsoft Fabric, Azure Data Factory, storage, and security
- Proven experience in tech/engineering lead or delivery lead roles
- Strong leadership, communication, and ownership mindset
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Data Engineer Lead employer: Ascendion
Ascendion is an exceptional employer that fosters a culture of innovation and collaboration in the heart of Greater London. With a strong emphasis on employee growth, we provide ample opportunities for professional development and engagement with senior stakeholders across diverse teams. Our commitment to agile methodologies and cutting-edge technology ensures that you will be at the forefront of cloud architecture and DevOps, making a meaningful impact in your role.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer Lead
✨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 Ascendion!
✨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 Data Engineer Lead at Ascendion.
✨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 Ascendion.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer Lead at Ascendion, 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 Data Engineer Lead
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 Ascendion, 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 Ascendion. 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 Ascendion
✨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 Ascendion!
✨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.
