Senior Data Engineer
- 5+ years of hands-on experience in business intelligence or IT management role in corporate or consulting setting
- Strong development background with experience in at least two scripting, object oriented or functional programming languages: SQL, Python, Java, Scala, C#, R
- Client stakeholder engagement and management
- Experience leading a work stream and managing small teams on Agile projects
- Data Warehousing experience, building operational ETL / ELT pipelines comprised of several sources, and architecting Data Models/Layers for Analytics
- Ability to work across structured, semi-structured, and unstructured data, extracting information and identifying linkages across disparate data sets
- Experience in multiple Database technologies: Traditional RDBMS (MS SQL Server, Oracle, MySQL, PostgreSQL), MPP (AWS Redshift, Oracle Exadata, Teradata, IBM Netezza), Distributed Processing (Spark, Hadoop, EMR), NoSQL (MongoDB, DynamoDB, Cassandra, Vertica, Neo4J, Titan)
- Experience developing solutions in Cloud platforms: Amazon Web Services, Microsoft Azure, Google Cloud Platform
- Experience generating Insights in the form of reports, KPIs, dashboards or ad-hoc queries; experience with Tableau is a bonus
- Ability to thrive in a lively project and consulting setting, often working on different and multiple projects at the same time
- Excellent interpersonal skills when interacting with clients, both verbally, email, written, and in a clear, timely, and professional manner
- Problem solving and brainstorming solutions to data integration and Analytics challenges
- Passion for developing your knowledge and skills in both the technical aspects of the Data Technology industry, and your personal and professional development in work and life
Who You'll Work WithYou will work in the London Headquarters of QuantumBlack. QuantumBlack help organisations make the most of data, analytics, and visualization to improve asset, operations, and human performance and productivity. You will join over 130 colleagues in London working in a variety of industries at the highest level within global enterprises, alongside McKinsey Analytics with over 800 advanced analytics practitioners. You will be working in cross-functional teams with other members of the Client Services, Engineering, Data Science, and Design teams.
What You'll Do
You will help our clients make the most of data, analytics, and visualization to improve asset, operations, and human performance and productivity.
You will architect and create data solutions across multiple technologies (RDBMS, Spark, Hadoop, NoSQL etc.) using a variety of languages (SQL, Python, R, Scala). We will provide comprehensive training to support you working with these technologies / languages. You will work on data analytics and visualisation consulting projects on complex and strategic business problems for large global enterprises.
You will be responsible for acting as the point of contact for our client's data owners and their domain experts, understanding their data systems and creating an inventory of their data ecosystem. You will model and map client data systems into a templated diagram and define and build data architectures.
You will support data scientists by creating views, queries, data extracts, variables, and features to help their analysis and maintain Information Security (IS) standards in regards to data exchange, storage, and processing. You will develop data exchange and ingestion plans with client IT/Data/IS stakeholders and create cloud and data environments for new projects using a mixture of Amazon Web Services, RDBMS, NoSQL, and Big Data / Hadoop platforms. We will support and help develop you in any of these technologies.
You will also architect and develop operational ETL solutions (using tools like Informatica, Alteryx, Dataiku etc), create Data Quality assessments and produce presentation-ready reports on client data systems, in addition to creating reusable custom scripts, queries, and code commands for ad hoc data processing tasks. You will learn and employ data visualization tools and basic Data Science techniques to analyse data and generate Insights whilst managing and developing Analyst Data Engineers on engagements.
Meet Some of McKinsey's Employees
Danielle is one of the leaders of McKinsey’s business with retail and consumer clients. She oversees client projects and helps her teams and her clients utilize McKinsey’s resources.
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