Oferta pracy

Data Engineer – Orpheus

McKinsey Knowledge Center Poland Sp. z o.o.About the company

  • plac Nowy Targ 28, Wrocław
    Wrocław, Lower Silesia
  • Offer expired 22 days ago
  • Remote recruitment
  • contract of employment
  • full-time
  • specialist (Mid / Regular), junior specialist (Junior)

McKinsey Knowledge Center Poland Sp. z o.o.

plac Nowy Targ 28


Your responsibilities

  • You will deliver and implement Orpheus solutions together with our strong delivery teams and in close collaboration with our McKinsey consulting teams, as well as directly with clients. A typical project involves the following steps: project scoping, data identification and extraction, data processing, engineering and enrichment, data cleansing and categorization, spend analysis and opportunity identification, handover, insights presentation and capability building.

  • As a Data Engineer you will support the data processing, engineering and enrichment phase. Leveraging proprietary and third-party ETL and data-transformation tools or scripts (e.g. Snaplogic, Talend, Alteryx, SQL, Python), you will merge various internal and external data tables and sources, perform data quality checks, and build up complex data models that build the basis for further data cleaning and analytics. Together with consulting teams, project managers and clients you will understand client and project requirements and discuss how to best implement new or customized analytics.

  • Another important part of your work is the continuous development and improvement of our proprietary data extractor and ETL tools. Here you will work closely with our Software Development and Data Science teams to create scalable solutions that can be brought to 100s of clients per year.

Our requirements

  • Undergraduate degree in Computer Science, Engineering, Mathematics, Information Systems or related field

  • Up to 3 years of relevant professional work experience in a data engineering function or with a reputed analytics firm

  • Strong coding knowledge in SQL, medium in T-SQL and Python is required

  • Understanding of data warehousing and data lake concepts, experience in building operational ETL data pipelines across a number of sources, and constructing relational and dimensional data models is required

  • Abilities in the field of large data handling through one or multiple of the following: Snaplogic, Talend, Alteryx is a plus

  • Experience with Microsoft SQL Server is a plus

  • Basic Java development skills, PowerShell or other scripting experience is a plus

  • Basic knowledge of version control systems (Git) is a plus

  • Experience in the field of procurement and/ or business intelligence is a plus

  • Solid problem-solving capabilities, including the ability to disaggregate issues, identify root causes and recommend solutions

  • Strong interpersonal, written/verbal communications skills in English

  • Willingness to travel (~20% of time)

McKinsey Knowledge Center Poland Sp. z o.o.

Orpheus, a McKinsey company, is McKinsey’s service line that brings technology and services to our clients to drive spend transparency, spend and cost analytics, and value-capture management. We are part of McKinsey’s global Client Capability Network (CCN), which includes more than 1,800 knowledge professionals who work alongside our consultants and clients to generate distinctive insights and proprietary knowledge.

You’ll be working with our global Orpheus team of software, analytics and procurement experts. You will be joining a fast-growing team in the procurement arena and taking cutting edge technology solutions to clients.

Orpheus infuses best-in-class technology and AI-based analytics with deep supply-market and category-sourcing expertise. You’ll be part of a team that is a core element of the digitally-enabled procurement function of the future. This will involve all business value chain activities from product development to distribution and playing a strategic role in managing budgets and costs, anticipating and mitigating supply risk, driving compliance, and generating transparency to external spend in an organization.

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