Data Engineer (AWS, Confluent & SnapLogic ) Siemens

2.0 - 7.0 years

4 - 9 Lacs

Bengaluru

Work from Office

We offer joint operations and digitalization services for Global Business Services and work closely alongside the entire Shared Services organization. We make efficient use of the possibilities of new technologies such as Business Process Management (BPM) and Robotics as enablers for efficient and effective implementations. We are looking for Data Engineer (AWS, Confluent & Snaplogic ) Data Integration : Integrate data from various Siemens organizations into our data factory, ensuring seamless data flow and real-time data fetching. Data Processing : Implement and manage large-scale data processing solutions using AWS Glue, ensuring efficient and reliable data transformation and loading. Data Storage : Store and manage data in a large-scale data lake, utilizing Iceberg tables in Snowflake for optimized data storage and retrieval. Data Transformation : Apply various data transformations to prepare data for analysis and reporting, ensuring data quality and consistency. Data Products : Create and maintain data products that meet the needs of various stakeholders, providing actionable insights and supporting data-driven decision-making. Workflow Management : Use Apache Airflow to orchestrate and automate data workflows, ensuring timely and accurate data processing. Real-time Data Streaming : Utilize Confluent Kafka for real-time data streaming, ensuring low-latency data integration and processing. ETL Processes : Design and implement ETL processes using SnapLogic , ensuring efficient data extraction, transformation, and loading. Monitoring and Logging : Use Splunk for monitoring and logging data processes, ensuring system reliability and performance. Youd describe yourself as: Experience : 3+ relevant years of experience in data engineering, with a focus on AWS Glue, Iceberg tables, Confluent Kafka, SnapLogic, and Airflow. Technical Skills : Proficiency in AWS services, particularly AWS Glue. Experience with Iceberg tables and Snowflake. Knowledge of Confluent Kafka for real-time data streaming. Familiarity with SnapLogic for ETL processes. Experience with Apache Airflow for workflow management. Understanding of Splunk for monitoring and logging. Programming Skills : Proficiency in Python, SQL, and other relevant programming languages. Data Modeling : Experience with data modeling and database design. Problem-Solving : Strong analytical and problem-solving skills, with the ability to troubleshoot and resolve data-related issues. Preferred Qualities: Attention to Detail : Meticulous attention to detail, ensuring data accuracy and quality. Communication Skills : Excellent communication skills, with the ability to collaborate effectively with cross-functional teams. Adaptability : Ability to adapt to changing technologies and work in a fast-paced environment. Team Player : Strong team player with a collaborative mindset. Continuous Learning : Eagerness to learn and stay updated with the latest trends and technologies in data engineering.

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