Position: Middle Big Data Engineer for a Business Services Company
Company: EPAM Systems (Anywhere)
Category: Data Science
Experience required: 2y
English level: upper
Published: 2021-09-01T00:00:00+03:00

The customer is a provider of high-quality business services in such areas as IT, Procurement, HR, Product Lifecycle Services, Financial Reporting and Analytics, and Real Estate and Facility Services.

The focus of the project is the migration and refactoring of existing applications to a special platform. The main task is to enable the production of valuable business insights.

Please note that even though you are applying for this position, you may be offered other projects to join within EPAM Anywhere.

**Responsibilities**
Understand requirements, clarify with BA and data analysts when necessary
Automating data ingestion processes
Enhance data sets by creating automated match rules
Automating data pre-processing, cleansing and verifying the integrity
Developing ETL transformations for data from various data sources (IQUVIA, SCOUT, SAP, unstructured files)
Working in a feature team of developers and test engineers, deliver results every sprint in accordance with sprint and release plans; report about activities via agreed project tools, timely report about risks/issues/dependencies, apply efforts to resolve and move the work forward
**Requirements**
2+ years of experience in Data Analytics
Strong skills in Big Data - ETL, Spark, Databricks, Redshift, S3, Python, SQL
Proficient working in AWS cloud environment
Ability to work independently as well as in a team of professionals, which may include not only EPAM colleagues, but also client’s engineers and managers as well as third-party vendors
**We offer**
Competitive compensation depending on experience and skills
Work on enterprise-level projects on a long-term basis
Full-time remote work
Unlimited access to learning resources (EPAM training courses, English classes, Internal Library)
Community of 38,000+ industry's top professionals