Our Data Engineers work closely with our clients and our Data Scientists in order to curate, transform and construct features which feed directly into our modelling approach.
This would be a hybrid client-facing/technical role using state of the art technologies, whilst also being able to communicate complex intractable ideas to non-technical audiences. Collecting clear requirements is a key part of this role and will define the technical strategy the team employs on the study.
Who you are
A core value at Digital McKinsey is fusion and at the heart of our multi-disciplinary teams is the belief that the sum of individual parts will always be less than the impact of the entire team. You are a highly collaborative individual who is capable of laying aside your own agenda, listening to and learning from colleagues, challenging thoughtfully and prioritising impact.
You search for ways to improve things and work collaboratively with colleagues. You believe in iterative change, experimenting with new approaches, learning and improving to move forward quickly. Trust between colleagues is paramount here – you are an individual who can always be trusted to work in the best interests of all colleagues and to achieve the best outcome for Digital McKinsey and our clients. You are naturally enthusiastic and enjoy sharing your passion with others.
You will work in multi-disciplinary environments harnessing data to provide real-world impact for organisations globally.
You will influence many of the recommendations our clients need to positively change their businesses and enhance performance.
- Work with our clients to model their data landscape, obtain data extracts and define secure data exchange approaches
- Acquire, ingest, and process data from multiple sources and systems into Big Data platforms
- Understanding, assessing and mapping the data landscape.
- Maintaining our Information Security standards on the engagement.
- Collaborate with our data scientists to map data fields to hypotheses and curate, wrangle, and prepare data for use in their advanced analytical models.
- Defining the technology stack to be provisioned by our infrastructure team.
- Building modular pipeline to construct features and modelling tables.
- Use new and creative techniques to deliver impact for our clients as well as internal R&D projects.
What you’ll learn
- How successful projections on real world problems across a variety of industries are completed through referencing past deliveries of end to end pipelines.
- Build products alongside the Core engineering team and evolve the engineering process to scale with data, handling complex problems and advanced client situations.
- Be focused on the wrangling, clean-up and transformation of data by working alongside the Data Science team which focuses on modelling the data.
- Using new technologies and problem-solving skills in a multicultural and creative environment.
You will work on the frameworks and libraries that our teams of Data Scientists and Data Engineers use to progress from data to impact. You will guide global companies through data science solutions to transform their businesses and enhance performance across industries including healthcare, automotive, energy and elite sport.
- Real-World Impact – No project is ever the same; we work across multiple sectors, providing unique learning and development opportunities internationally.
- Fusing Tech & Leadership – We work with the latest technologies and methodologies and offer first class learning programmes at all levels.
- Multidisciplinary Teamwork - Our teams include data scientists, engineers, project managers, UX and visual designers who work collaboratively to enhance performance.
- Innovative Work Culture – Creativity, insight and passion come from being balanced. We cultivate a modern work environment through an emphasis on wellness, insightful talks and training sessions.
- Striving for Diversity – With colleagues from over 40 nationalities, we recognise the benefits of working with people from all walks of life.
- Meaningful experience with at least two of the following technologies: Python, Scala, SQL, Java
- Commercial client-facing project experience is helpful, including working in close-knit teams
- Ability to work across structured, semi-structured, and unstructured data, extracting information and identifying linkages across disparate data sets
- Meaningful experience in multiple database technologies such as Distributed Processing (Spark, Hadoop, EMR), Traditional RDBMS (MS SQL Server, Oracle, MySQL, PostgreSQL), MPP (AWS Redshift, Teradata), NoSQL (MongoDB, DynamoDB, Cassandra, Neo4J, Titan)
- Ability to clearly communicate complex solutions
- Deep understanding of Information Security principles to ensure compliant handling and management of client data
- Experience and interest in Cloud platforms such as: AWS, Azure, Goole Platform or Databricks
- Confirmed experience in traditional data warehousing / ETL tools (Informatica, Talend, Pentaho, DataStage)
- Extraordinary attention to detail
- Strong command of English language (both verbal and written)
- Ability to travel 50% of the time