Data Engineer - Quantumblack job from McKinsey & Company in Rio de Janeiro, RJ, Brazil

You will join QuantumBlack’s leading data engineering team in São Paulo. You will gain experience working in interdisciplinary teams consisting of Data Scientists, Data Engineers, Designers and McKinsey experts.

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 QuantumBlack 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 QuantumBlack and our clients. You are naturally enthusiastic and enjoy sharing your passion with others.

You will work closely with our clients and Data Scientists to transform and construct features which feed directly into our data science and machine learning modelling approaches.

Our Data Engineers lay the foundations for the Data Science process, wrangling disparate sources into tidy data. This role will allow you to really gain knowledge in building data pipelines, wrangling and feature engineering all whilst being exposed to the latest techniques.

Our projects cover a wide range of industries and may expose you to problem areas such as: Disease epidemiology, athlete injury prediction or salesforce effectiveness optimisation and many more. In order to gain insight from previously ignored and unconnected data you will need to extract information from vast array of different data sources such as: Data Warehouses, SQL databases, legacy applications, unstructured data, documents, emails, APIs, Kafka endpoints and graph databases.

Role responsibilities

• 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 projects 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.

Our projects range from helping pharmaceutical companies bring lifesaving drugs to market quicker to optimising a Formula1 car’s performance. At QuantumBlack you have the best of both worlds; all the benefits of being part of one of the leading management consultancies globally and the autonomy to thrive in a fast growth tech culture:

• Healthcare Efficiency – We helped a healthcare provider improve their clinical trial practices by identifying congestion in diagnostic testing as a key indicator of admissions breaches.
• Environmental Impact – We designed and built the first data-driven application for a state of the art centre of excellence in urban innovation by collecting real-time data from environmental sensors across London and deploying proprietary analytics to find unexpected patterns in air pollution.
• Product Development – We worked with the CEO of an elite automotive organisation to reduce the 18-month car development timeframe by improving processes, designs and team structures.

• Bachelor's or master's degree in computer science or similarly relevant field
• 2+ years of experience as a full stack software engineering working with modern tools and a preference for backend code
• Strong experience coding (Python, Scala, Java) and working with a variety of relational DBs
• Knowledge in creating end-to-end data pipelines for the purpose of creating production-grade machine learning systems using open source tools such as Python, Pandas, pySpark, Kedro, Airflow and more
• Interest in the latest big data technologies like Spark, Presto, Neo4j
• Excited about using data to solve a variety of business problems and working in cross-functional teams of experts
• Ability in clearly communicating complex solutions
• Strong command of English language (both verbal and written)