At a Glance
- Tasks: Transform raw data into powerful insights and build scalable data solutions.
- Company: Join a forward-thinking team in the Public Sector Business unit.
- Benefits: Enjoy 25 days off, wellness support, and a collaborative work environment.
- Other info: Continuous learning opportunities and exciting project work that makes a difference.
- Why this job: Be at the forefront of data innovation and make a real impact.
- Qualifications: Proficiency in SQL, Python, and experience with Power BI dashboards.
The predicted salary is between 56700 - 69300 £ per year.
- Methods Analytics (MA) is recruiting for a Data Engineer to join our team within the Public Sector Business unit on a permanent basis
- Work closely with cross-functional teams, translating complex technical concepts into clear, accessible language for non-technical audiences and aligning data solutions with business needs
- Collaborate with a dynamic delivery team on innovative projects, transforming raw data into powerful insights that shape strategic decisions and drive business transformation
- Utilise platforms and tools such as Microsoft Fabric, Azure Data Factory, Azure Synapse, Databricks, and Power BI to build robust, scalable, and future-proof end-to-end data solutions
- Design and implement efficient ETL and ELT pipelines, ensuring seamless integration and transformation of data from various sources to deliver clean, reliable data
- Develop and maintain sophisticated data models, employing dimensional modelling techniques to support comprehensive data analysis and reporting
- Implement and uphold best practices in data governance, security, and compliance, using tools like Azure Purview, Unity Catalog, and Apache Atlas to maintain data integrity and trust
- Ensure data quality and integrity through meticulous attention to detail and rigorous QA processes, continually refining and optimising data queries for performance and cost-efficiency
- Develop intuitive and visually compelling Power BI dashboards that provide actionable insights to stakeholders across the organisation
- Monitor and tune solution performance, identifying opportunities for optimisation to enhance the reliability, speed, and functionality of data systems
- Stay ahead of industry trends and advancements, continuously enhancing your skills and incorporating the latest Data Engineering tools, languages, and methodologies into your work
• Your Impact
- Enable business leaders to make informed decisions with confidence by providing them with timely, accurate, and actionable data insights
- Be at the forefront of data innovation, driving the adoption and understanding of modern tooling, architectures, and platforms
- Deliver seamless and intuitive data solutions that enhance the user experience, from real-time streaming data services to interactive dashboards
- Play a key role in cultivating a data-driven culture within the organisation, mentoring team members, and contributing to the continuous improvement of the Engineering Practice
Benefits
- Autonomy to develop and grow your skills and experience
- Be part of exciting project work that is making a difference in society
- Strong, inspiring and thought-provoking leadership
- A supportive and collaborative environment
- Development access to Linked In Learning, a management development programme and training
- Wellness 24/7 Confidential employee assistance programme
- Social - Breakfast Tuesdays, Pizza Thursday monthly, weekly social in the office and commitment to charitable causes
- Time off 25 days a year
- Pension Salary Exchange Scheme with 4% employer contribution and 5% employee contribution
- Discretionary Company Bonus based on company and individual performance
- Life Assurance of 4 times base salary
- Private Medical Insurance which is non-contributory (spouse and dependants included)
- Worldwide Travel Insurance which is non-contributory (spouse and dependants included)
- Benefits Platform offering various retail and leisure discounts
- Efficiency in Query Writing: You can craft and optimise queries to be both cost-effective and high-performing, ensuring fast and reliable data retrieval
- Experience in Power BI Dashboard Development: You possess experience in creating insightful and interactive Power BI dashboards that drive business decisions
- Strong Communication Skills: Ability to effectively translate complex technical topics into clear, accessible language for non-technical audiences
- Proficiency in SQL and Python: You are highly proficient in SQL and Python, enabling you to handle complex data problems with ease
- Business Requirements Translation: You have a knack for understanding business requirements and translating them into precise technical specifications that guide data solutions
- Hands-On Experience with Spark-Based
Solutions: You possess experience with Spark-based platforms like Azure Synapse, Databricks, Microsoft Fabric, or even on-premise Spark clusters, using Py Spark or Spark SQL to manage and process large datasets
- Continuous Learning and Development: Commitment to continuous learning and professional development, staying up to date with the latest industry trends, tools, and technologies
- CI/CD Mindset: You naturally work within Continuous Integration and Continuous Deployment (CI/CD) environments, ensuring automated builds, deployments, and unit testing are integral parts of your development workflow
- Expertise in Building ETL and ELT Pipelines: You are skilled in building robust ETL and ELT pipelines, mostly in Azure, utilising Azure Data Factory and Spark-based solutions to ensure efficient data flow and transformation
- Proficiency in Dimensional Modelling: You are adept at applying dimensional modelling techniques, creating efficient and effective data models tailored to business needs
- Understanding of Data Lakehouse Architecture: You have a strong grasp of the principles and implementation of Data Lakehouse architecture
- This role will require you to have or be willing to go through Security Clearance
- Understanding of
- Agile
- Development
Methodologies: Familiarity with iterative and agile development methodologies such as SCRUM, contributing to a flexible and responsive development environment
- Knowledge of Data Governance Tools: Experience with data governance tools like Azure Purview, Unity Catalog, or Apache Atlas to ensure data integrity and compliance
- Experience with High-Performance
- Data
Systems: Handling large-scale data systems with high performance and low latency, such as managing 1 billion+ records or terabyte-sized databases
- Understanding of SOLID Principles: Familiarity with the SOLID principles of object-oriented programming
- Experience with Public Sector Clients: Experience working with public sector clients and understanding their specific needs and requirements
- Exposure to Streaming/Event-Based
Technologies: Experience with technologies such as Kafka, Azure Event Hub, and Spark Streaming for real-time data processing and event-driven architectures
- Knowledge of Delta Tables or Apache Iceberg: Understanding and experience with Delta Tables or Apache Iceberg for managing large-scale data lakes efficiently
- Experience with Data for Data Science/AI/ML: Experience working with data tailored for data science, AI, and ML applications, Familiarity with
- Recent
Innovations: Knowledge of recent innovations such as Gen AI, RAG, and Microsoft Copilot, as well as certifications with leading cloud providers and in areas of data science, AI, and ML
- Exposure to Microsoft Fabric: Familiarity with Microsoft Fabric and its capabilities would be a significant advantage
- #J-18808-Ljbffr
Senior Data Engineer (Fabric-Platforms) employer: Methods
Methods is an exceptional employer, offering a dynamic and supportive work culture that prioritises collaboration and innovation. With a strong focus on employee development through access to training and wellness programmes, team members are empowered to grow their skills while contributing to meaningful projects that positively impact society. The hybrid working model and commitment to work-life balance further enhance the appeal of joining this forward-thinking consultancy.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer (Fabric-Platforms)
✨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 Methods!
✨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 Senior Data Engineer (Fabric-Platforms) at Methods.
✨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 Methods.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Engineer (Fabric-Platforms) at Methods, 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 Senior Data Engineer (Fabric-Platforms)
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 Methods, 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 Methods. 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 Methods
✨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 Methods!
✨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.
