Hybrid Senior Data Engineer @ IDBC Creative Solutions Kft.
2 days ago
As a Senior Data Engineer, you will design, build, and manage data pipelines that support data-driven decision making and machine learning across various products and services. You will collaborate with stakeholders to understand data requirements, model data flows, transform raw data, ensure data quality, and comply with data governance standards. You will use your skills and experience in software engineering, cloud data engineering, data platforms, and data visualization to deliver scalable and reliable data solutions.
- Experience in data engineering, data science, software development, or data modeling
- In-depth experience in programming languages, such as Python, Java, Scala, or C#
- Experience with Microsoft Azure data platform
- Experience with data tools and frameworks, such as Databricks, Spark, Kafka
- Experience with SQL data query language
- Experience with Azure Data Lake, Azure Data Factory
- Experience with data governance and compliance standards, such as GDPR
- Bachelor's or Master's degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field
As a Senior Data Engineer, you will design, build, and manage data pipelines that support data-driven decision making and machine learning across various products and services. You will collaborate with stakeholders to understand data requirements, model data flows, transform raw data, ensure data quality, and comply with data governance standards. You will use your skills and experience in software engineering, cloud data engineering, data platforms, and data visualization to deliver scalable and reliable data solutions.
,[Collaborate across squads to define data requirements, roadmaps, use cases, and metrics for data products or features, Design and document data models, schemas, and flows that meet business and analytical needs, Extract, transform, and load data from various sources using query languages, tools, and APIs, Ensure data quality, completeness, and reliability across data pipelines, Develop and implement data tools, tests, and monitors to optimize data performance and troubleshoot issues, Comply with data governance policies and standards for data security, privacy, and classification, Contribute to the data glossary and data catalog to document data sources, definitions, and lineage] Requirements: Spark-
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