Staff Data Engineer
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Die Stelle
Design, develop, and maintain an enterprise-scale Big Data and Analytics platform spanning on-premises and cloud environments.
Key components include Hadoop ecosystem (HDFS, MapReduce, Yarn), HBase, Hive, and Spark to build data lakes and analytics-ready pipelines.
Ensure data integrity and security, manage patching and vulnerability remediation, and apply best practices for data governance.
Lead data warehousing and lakehouse efforts with Snowflake, SQL Server, and Databricks, and implement ETL workflows with SSIS, Airflow, and related tools.
Collaborate with cross-functional teams, manage cloud subscriptions across Azure, GCP, and AWS, and drive platform optimization and technology adoption.
Demonstrate strong problem-solving, communication, and documentation skills to contribute to a high-impact data engineering practice.
Key components include Hadoop ecosystem (HDFS, MapReduce, Yarn), HBase, Hive, and Spark to build data lakes and analytics-ready pipelines.
Ensure data integrity and security, manage patching and vulnerability remediation, and apply best practices for data governance.
Lead data warehousing and lakehouse efforts with Snowflake, SQL Server, and Databricks, and implement ETL workflows with SSIS, Airflow, and related tools.
Collaborate with cross-functional teams, manage cloud subscriptions across Azure, GCP, and AWS, and drive platform optimization and technology adoption.
Demonstrate strong problem-solving, communication, and documentation skills to contribute to a high-impact data engineering practice.
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