General Information

Data Engineer | Data & AI Practice | Risk Advisory
Work arrangement
Risk Advisory
Area of interest
Data & Analytics, Engineering
Way of work

Description & Requirements

Who we are looking for
  • Bachelor/engineer degree (preferred computer science, statistics, mathematics, econometrics, or any related field)
  • 2+ years of professional experience in implementing/delivering data services
  • Experience with cloud data environments (one of GCP, AWS, Azure)
  • Extensive experience with SQL, ETL and data transformation techniques and patterns
  • Working experience with OLAP, Dimensional Modeling, Transactional data, normalization
  • Interest in Big Data ecosystem and frameworks (Apache Beam, MapReduce, Spark, Kafka and Databricks) would be a plus.
  • Familiarity with NoSQL databases (e.g. MongoDB, Cassandra, HBase, Elasticseach) would be a plus.
  • Passion to grow and learn
  • Team-player mindset
  • Good level of English
Your future role
  •  Build scalable, highly performant cloud-based solutions for integrating a variety of raw data sources, serving as a solid foundation for data loading and transformation problems.
  • Develop and deploy batch & real-time data integration solutions, ETL processes, automated workflows that ingest data from both internal databases and external sources to manipulate, map and feed them into staging and dimensional model layers.
  • Design, implement and enhance conceptual, logical and physical data models, i.e. database architectures and views addressing particular needs of analytics and data science.
  • Working with clients throughout the whole project cycle (Business understanding, Data understanding, Modeling, Evaluation and Deployment)
  • Cooperation with subject matter experts from risk advisory and technical consultants to jointly deliver high quality projects for the customers
What we offer
  • A clear career path and Career Coach, who will guide you through the organization and your opportunities
  • Wide range of trainings and knowledge development opportunities, including financing of your certificates and workshops in a chosen career specialization
  • A unique opportunity to develop the AI career with a great team of experienced peers and cooperation with Deloitte AI Institute
  • Challenging tasks with the freedom of action in your field
  • Friendly team atmosphere, flexible working set-up and excellent working conditions
Selection process
Recruitment Journey
I stage – we will carefully read your resume

II stage – you will be asked to complete an analytical and English online test

III stage – you we be invited for HR interview

IV stage - you we be invited for Hiring Manager interview (interview contains case study)

Recruiter tips

We want job seekers exploring opportunities at Deloitte to feel prepared and confident. We suggest you to do your research: know some background about the organization and the business area you’re applying to. Moreover we advise you to brush up on your behavioral and case interviewing skills and practice discussing your experience and job history with a family member, friend or mentor.
About Deloitte
Deloitte is a variety of people, experience, industries and services we deliver in 150 countries of the world. It is an intellectual challenge, a good starting point for your career, and an excellent opportunity for continuous development and gaining valuable life experiences. What you only must do is to take the first step – press the apply button and send us your CV, go through all the stages of the recruitment process and sign a contract with us. Deloitte is simply your best choice.
About the team
Data & AI Team focuses on the practical applications of data analytics and artificial intelligence. Broadly understood risk management is a key area of companies' activity, covering both well-known applications such as credit scoring, fraud analytics or market risk analytics, but also new areas such as deepfakes detection, cyber intrusion, climate risk analytics, dynamic risk scoring. We also deal with the most important areas determining the success of implementations, such as AI explainability or AI fairness, and we take part in discussions on the regulation of the AI market in the European Union.