Description
The team contributes to data governance, quality assurance, and the development of robust data platforms that support reliable data-driven decision-making.
Responsibilities
•Contribute to data governance processes, including data preparation, generation, obfuscation, integration, slicing, and quality control
•Prepare test datasets and perform data profiling and benchmarking
•Test data ingestion pipelines, ETLs, APIs, and integrations
•Participate in designing and maintaining data platforms and a data quality automation framework
•Maintain QA environments and contribute to establishing the CI/CD process
•Support customer inquiries about data quality issues and data consumption
Requirements
•1+ Years of hands-on engineering experience and practice in Data Management, Data Quality verification/Data Governance, or Data Integration
•Understand data ingestion pipelines, Data Lakes, ETL testing, and DWH basics
•Know CI/CD principles and best practices in data processing
•Proficiency in SQL
•Knowledge of Python or other scripting languages
•Experience with AWS, Azure, or GCP
•Understand test automation
•Experience in data analysis and requirements validation
•Experience in test case design and bug reporting
•Analytical approach to problem-solving and excellent interpersonal and communication skills
•English proficiency at B2 level or higher
Nice to have
•Knowledge of Spark, Hadoop, Kafka, ElasticSearch, or Python libraries such as Pandas and NumPy
•Understanding of ETL tools such as Databricks and Big Data principles
•Familiarity with Linux and Bash scripting basics
•Experience in data visualization testing and maintaining QA environments
•Understanding of data project test strategy creation and test planning
Conditions
No conditions specified in the posting.
