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- Tasks: Join our FinanceBI team to build and optimize data pipelines and warehouses.
- Company: L.E.K. Consulting is a global strategy firm with a strong track record in various industries.
- Benefits: Collaborative work environment, opportunities for growth, and exposure to cutting-edge technologies.
- Why this job: Be part of a dynamic team solving critical business problems while enhancing your data engineering skills.
- Qualifications: Bachelor's degree in a related field and 3-5 years of data engineering experience required.
- Other info: Experience with Azure and Microsoft BI tools is a plus!
The predicted salary is between 43200 - 72000 £ per year.
London Office – Data Engineer – Global Finance team
Location: London
About L.E.K.
L.E.K. Consulting is a global strategy consulting firm with offices across Europe, the Americas, and Asia-Pacific. We advise clients on their key strategic issues, leveraging our deep industry expertise and analytical rigor to help them make informed decisions and solve their toughest and most critical business problems. L.E.K. provides a comprehensive range of capabilities around the globe, including Strategy, Mergers & Acquisitions, and Performance Improvement. We have deep expertise and a proven track record in a broad range of industries.
Founded in London in 1983, we now employ more than 1,600 professionals worldwide across 23 offices.
Position Summary
The Data Engineer will collaborate with and support the FinanceBI and global finance team in building our Data Warehouse. They will be required to develop scalable data pipelines, extracting data from core systems, transforming it, and loading it into database/warehouse tables while also ensuring these are optimized for maximum performance within the tools available. They are expected to have strong collaboration skills and be a high performer within the FinanceBI team.
Responsibilities
- Design and develop data transfer engines and pipelines: highly scalable, end-to-end processes to consume, integrate, and analyze data from different data sources.
- Perform data collection, cleansing, and integration for analytical needs.
- Optimize storage and retrieval processes for maximum performance and efficiency.
- Optimize data transfer engines and pipelines by monitoring, evaluating performance, and applying enhancements.
- Design and develop data marts and define data models.
- Participate in System Data Architecture and Data Governance activities.
- Adhere to and take part in the enhancement of data management standards, coding standards, guidelines, and policies.
- Employ a strong engineering mindset in the design and development of automated monitoring, alerting, and recovery processes.
- Collaborate with Source System analysts, Business Intelligence developers, Architects, and Stakeholders to ensure that requirements for integration, security, quality, and cross-functional usage are addressed.
- Help resolve data issues, troubleshoot system problems, and assist with reporting, debugging data accuracy issues, and other related functions.
- Work in a collaborative environment—meetings, iterative development, and design and code review sessions.
- Collaborate with all technology and business functions to understand requirements and produce clear specifications and documentation.
- Implement quality checks and troubleshoot issues to ensure data accuracy and reliability.
- Monitor and manage the performance of data systems.
- Stay updated on emerging technologies and trends in data engineering.
Key Skills:
- Strong analytical and problem-solving skills.
- Process and solution-oriented with great documentation skills.
- Attention to detail.
- Teamwork skills.
- Written and verbal communication skills.
- Interpersonal skills.
- Flexibility.
- Adaptability.
- Initiative – self-starter, driven, owns tasks with minimal supervision.
- Delivery-driven – can work to defined timelines.
Qualifications / Experience:
- Minimum bachelor’s degree in Computer Science, Data Engineering, Information Technology, or a related field.
- 3-5 years of experience as a Data Engineer or a similar role.
- Expert knowledge of data engineering tools and technologies (e.g., SQL, ETL, data warehousing).
- Proficiency in T-SQL (4+ years of SQL experience).
- 4+ years of experience with schema design and dimensional data modeling.
- Proficiency in the Microsoft BI Tool Stack; Database, SSIS, SSAS, PowerBI (Nice to Have).
- Experience with Azure cloud platform and Azure Data Factory.
- Knowledge of data modeling, database design, and data governance.
- Experience with Continuous Integration Processes and Tools (AzureDevOps).
- Experience with Change Management Processes and Cycles (Release and Deployment).
- Experience with Microsoft SQL Data Tools (2019+).
- Experience in working in Development Teams and Team Collaborative tools (Jira or similar).
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London Office- Data Engineer - Global Finance team employer: LEK
Contact Detail:
LEK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land London Office- Data Engineer - Global Finance team
✨Tip Number 1
Familiarize yourself with the specific data engineering tools and technologies mentioned in the job description, such as SQL, ETL, and data warehousing. Having hands-on experience or projects that showcase your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Highlight your experience with Azure cloud platform and Azure Data Factory. If you have worked on any relevant projects, be ready to discuss them in detail during the interview to demonstrate your practical knowledge.
✨Tip Number 3
Showcase your teamwork and collaboration skills by preparing examples of how you've successfully worked in a team environment. This role emphasizes collaboration, so being able to illustrate your ability to work well with others will be crucial.
✨Tip Number 4
Stay updated on emerging technologies and trends in data engineering. Being knowledgeable about the latest advancements can help you engage in meaningful conversations during interviews and show your commitment to continuous learning.
We think you need these skills to ace London Office- Data Engineer - Global Finance team
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the Data Engineer role. Focus on your expertise in data engineering tools, SQL, and any experience with Azure or Microsoft BI Tool Stack.
Craft a Strong Cover Letter: Write a cover letter that showcases your passion for data engineering and your understanding of L.E.K. Consulting's work. Mention specific projects or experiences that demonstrate your problem-solving skills and ability to collaborate effectively.
Showcase Your Technical Skills: In your application, emphasize your technical skills, particularly in T-SQL, ETL processes, and data warehousing. Provide examples of how you've used these skills in previous roles to solve complex data challenges.
Highlight Collaboration Experience: Since the role requires strong teamwork skills, include examples of past collaborative projects. Describe how you worked with cross-functional teams to achieve common goals, especially in data-related tasks.
How to prepare for a job interview at LEK
✨Showcase Your Technical Skills
Be prepared to discuss your experience with data engineering tools and technologies, especially SQL and ETL processes. Highlight specific projects where you developed scalable data pipelines or optimized data storage solutions.
✨Demonstrate Collaboration Abilities
Since the role requires strong teamwork skills, be ready to share examples of how you've successfully collaborated with cross-functional teams. Discuss any experiences where you worked closely with analysts, developers, or stakeholders to meet project goals.
✨Emphasize Problem-Solving Skills
Prepare to talk about challenges you've faced in previous roles and how you approached solving them. Use the STAR method (Situation, Task, Action, Result) to structure your responses and clearly illustrate your analytical mindset.
✨Stay Updated on Industry Trends
Show your enthusiasm for the field by discussing recent trends or emerging technologies in data engineering. This demonstrates your commitment to continuous learning and staying relevant in a fast-evolving industry.
