At a Glance
- Tasks: Build and maintain data pipelines, ensuring data governance and quality.
- Company: Join a fast-paced company leading the way in zero-emission solutions.
- Benefits: Enjoy bonuses, flexitime, healthcare, and career progression opportunities.
- Other info: Dynamic environment with opportunities to work on innovative projects.
- Why this job: Be part of a pioneering data centre and make a real impact.
- Qualifications: 3+ years in data engineering with experience in cloud platforms.
The predicted salary is between 50000 - 50000 £ per year.
Join a fast-paced, high-growth company at the forefront of zero-emission solutions, as they look for a skilled and motivated Microsoft Data Engineer who owns how data moves across the business.
Why This Role
This company is building out a data centre of excellence and having recently hired a Head of Digital and an Infrastructure Architect, this is the first of a number of Data Engineer positions they are looking to fill in the very near future. If you are someone who takes ownership of data governance and is not just focused on report-building, then this is a fantastic opportunity for you to join an organisation at the beginning of this journey.
What You Will Be Doing
- Build and maintain pipelines that bring data together from across the business into a central platform such as Microsoft Fabric.
- Profile, validate and cleanse incoming data.
- Develop ELT/ETL processes using tools such as dbt, Power Query (M), Spark, Azure Data Factory or Fabric Data Pipelines.
- Design dimensional models and reusable models that capture business logic once and serve it consistently to every downstream tool.
- Author efficient transformations in SQL, dbt or DAX for metrics such as year-on-year change, rolling averages and cohort analysis.
- Build automated tests and data-quality checks so issues are caught before they reach a report.
- Monitor pipeline and refresh runs, troubleshoot failures, and meet agreed SLAs.
- Tune platform performance and cost using partitioning, aggregations, query optimisation and appropriate storage/compute choices.
- Manage deployment across environments and support CI/CD and DataOps pipelines for releases and rollback.
- Build and certify trusted datasets and semantic models so business users can safely explore data and build their own reports across whichever tools suit them such as Power BI, Fabric, Excel, etc.
- Produce clear, well-laid-out visuals that reduce decision lag and help teams act quickly.
What You Will Have
- Third-level qualification in Computer Science, Information Systems, Data, Software Engineering or any other related discipline.
- 3+ years experience focused on data engineering and modelling.
- Experience building data pipelines and models that integrate three or more major data sources.
- Experience working with large datasets.
- Hands-on delivery with at least one modern cloud data platform, eg. Microsoft Fabric, Databricks, Synapse or BigQuery.
- Experience building governed self-service and semantic layers that enable other teams to report independently.
Skills: Databricks, Microsoft Fabric, SQL, Data Governance, Azure
Benefits: Bonus, Flexitime, Healthcare, Career Progression, Discount with local businesses
Microsoft Data Engineer - Help Build Out Data Centre of Excellence TLNT1_NI in Belfast employer: IrishJobs
Join a pioneering company dedicated to zero-emission solutions, where as a Microsoft Data Engineer, you will play a crucial role in shaping the data centre of excellence. With a strong emphasis on employee growth, flexible working hours, and a supportive work culture, this organisation not only values your contributions but also invests in your career progression. Enjoy unique benefits such as healthcare and discounts with local businesses while being part of a team that is committed to innovation and sustainability.
StudySmarter Expert Advice🤫
We think this is how you could land Microsoft Data Engineer - Help Build Out Data Centre of Excellence TLNT1_NI in Belfast
✨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 IrishJobs!
✨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 Microsoft Data Engineer - Help Build Out Data Centre of Excellence TLNT1_NI at IrishJobs.
✨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 IrishJobs.
✨Apply Directly through Our Website
When you find a suitable opening like Microsoft Data Engineer - Help Build Out Data Centre of Excellence TLNT1_NI at IrishJobs, 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 Microsoft Data Engineer - Help Build Out Data Centre of Excellence TLNT1_NI in Belfast
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 IrishJobs, 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 IrishJobs. 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 IrishJobs
✨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 IrishJobs!
✨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.
