Data Engineer for Master Data Architecture
3 days ago
We are seeking a highly skilled Data Engineer to join our team at emagine Sp. Z o.o. as part of our Master Data Management project.
Key Responsibilities:- Design and implement robust data models for each domain, ensuring data quality and consistency.
- Develop and maintain ETL processes using SQL and Oracle to extract, transform, and load data into the new Master Data source.
- Collaborate with business stakeholders to understand key business needs and identify opportunities for process simplification and automation.
- Set up data governance and implement data governance recipes for the new data source.
- Establish data life cycle management for the new data source.
- Implement data quality assurance processes to ensure data accuracy and completeness.
- Design and develop APIs and Kafka interfaces to expose data to consumers.
- Expert knowledge in relational database management systems (RDBMS), preferably SQL and Oracle.
- Good understanding of data and its use in the organization.
- Experience with different tool configurations.
- Familiarity with Apache Kafka as a distribution channel.
- Basic understanding of application programming interfaces (APIs).
- English fluency – verbal and written.
- Ability to quickly capture and understand things, with the ability to have a wider perspective and transform it into development items.
- Ability to work in a fast-paced environment, delivering on milestones and in an agile environment.
This project aims to enhance business ownership for data by involving business areas in the work, establish a single trusted source for Master & Reference data, and consolidate relevant data from multiple domains and sources.
The goals of the project include eliminating alternative data sources, creating product visions describing the target state for the data, creating robust but flexible business data models, establishing data governance, setting up data quality assurance, setting up data life cycle management, simplifying and automating related E2E business processes, exposing data to consumers via standard API/Kafka interface, retiring irrelevant data, and preparing for decommissioning of legacy Master and Reference data system MDN.
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