London Office - Data Engineer - Global Finance teamLocation: 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 SummaryThe 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.
ResponsibilitiesDesign 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 enhancement of data management standards, coding standards, guidelines, and policies.Employ strong engineering mindset in 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 as needed, 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 specification 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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