middle data quality engineer for a business services company
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.
- 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
- 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
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