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Middle Data Quality Engineer for a Business Services Company

Colombia
Python.Core, SQL, General Management

We are currently looking for a remote Middle Data Quality Engineer with 2+ years of experience in Data Quality Engineering and advanced Data Analysis skills using T-SQL, Python to join our team.

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.

Responsibilities
  • Design, lead, and manage a data implementation strategy
  • Manage and maintain data assets in alignment with data management processes
  • Ensure data governance and compliance through appropriate processes
  • Participate in mapping business data sources to appropriate repositories of data
  • Identify new critical data elements and metadata
  • Coordinate and ensure the implementation of data asset management standards and policies in close collaboration with the providers of the data
  • Accountable for data discrepancies and mitigation, data availability and consistency
  • Drive compliance risk mitigations for regional data privacy and security
  • Participate in mapping business data needs to appropriate sources of data; provide guidance and coordinate/resolve data issues
  • Collaborate with internal data governance teams and ensure the implementation of data governance and data asset management standards and policies
Requirements
  • 2+ years of experience in Data Quality Engineering
  • Advanced Data Analysis using T-SQL, Python (familiarity with Pandas); should be able to write complex scripts
  • Expert at doing Data Profiling and documenting the results
  • Expert at identifying common data issues related to data types, formats, missing values, duplicate data, etc.
  • Concrete experience working with various file formats more specifically CSV, Parquet, Any other Delimited, XML, JSON
  • Expert at working with relational tables in SQL Server Management Studio
  • Good understanding of time series and historical data. Good understanding
  • Good understanding of OLTP (Normalized tables in 3NF) and OLAP (Star Schema and Snowflake schema dimension and fact tables) systems
  • Familiarity with various encodings like ASCII and UNICODE and their implications on data quality
  • Good understanding of QA and Testing best practices
  • Be able to create test plans and test cases to do end-to-end testing of data pipelines, and appropriately identify data quality issues, and document them for bug fixes; once the bugs are fixed should be able to go back and do regression testing
  • Good with designing test harness for automated testing
  • Ideally good exposure to Azure DevOps
  • Good understanding of various ETL Tools especially ADF and Databricks
  • English level proficiency B1
Benefits
  • International projects with top brands
  • Work with global teams of highly skilled, diverse peers
  • Healthcare benefits
  • Employee financial programs
  • Paid time off and sick leave
  • Upskilling, reskilling and certification courses
  • Unlimited access to the LinkedIn Learning library and 22,000+ courses
  • Global career opportunities
  • Volunteer and community involvement opportunities
  • EPAM Employee Groups
  • Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn