Siemens Energy

How You’ll Make an Impact

• Designing and implementing scalable, secure, and high-performance Database/data warehouse-based platform and solutions
• Designing and specifying the overall database/data warehouse structure based on functional and technical requirements.
• Developing logical and physical data models
• Developing strategies for data acquisition, archive recovery, and database implementation
• Manage data structures, performance management and tuning, data ingest into the databases, system monitoring, capacity management, availability management, backup and restore.
• Ensuring compliance with security and data protection policies.
• Implement hands on proof of concepts aimed towards automation and improvement of the data platform.

What You Bring

• Bachelor’s Degree or higher in Computer Science or a related technical field.
• 5+ years of experience with at least 3 years as Data Engineer in high volume ETL/Data Warehousing projects
• Strong RDMBS Skills and experience with PostgreSQL and Snowflake.
• Extensive experience in development, operations, and administration of Data Warehouse solutions.
• Experience with ETL solutions (preferably Airflow) in a complex, high-volume data environment.
• Knowledge of DevOps concepts and experience with continuous integration and continuous delivery (CI/CD) tools
• Strong data analysis skills.
• Knowledge of AWS services such as Lambda, SQS, SNS.

About the Team

Our team belongs to the Digital Products and Solutions Function within Siemens Energy. Our mission is to grow the digital software business and develop solutions and products for both internal and external customers.

These solutions include Edge Computing and applications, On-site sensor technology integration, Cloud-based platforms and cloud-based software solutions and applications.

The solutions, applications, and platforms we provide allow data acquired to be used to improve the operation and maintenance of power plants and industrial facilities of all sizes this includes the development of digital twins, analytics platforms and agents, artificial intelligent and machine learning applications and algorithms.