Staff Business Data Engineer

As a Staff Business Data Engineer at our Valves team, you will play a crucial role in shaping the future of energy technology using data. You will work at the core of digital transformation, collaborating with teams to solve technical challenges and design innovative solutions. Key Responsibilities: - Designing and implementing scalable and robust data pipelines for collecting, processing, and storing data from various sources. - Developing and maintaining data warehouse and ETL processes for data integration and transformation. - Optimizing data systems' performance to ensure efficient processing and analysis. - Collaborating with product managers and analysts to understand data requirements and implement solutions for data modeling and analysis. - Identifying and resolving data quality issues to ensure accuracy, consistency, and completeness. - Implementing and maintaining data governance and security measures for sensitive data protection. - Monitoring and troubleshooting data infrastructure, performing root cause analysis, and implementing necessary fixes. - Ensuring the use of state-of-the-art methodologies for productive and effective job execution, including researching new technologies in data acquisition and analysis. Qualifications Required: - Bachelors or higher degree in Computer Science, Information Systems, or a related field. - 6-10 years of experience as a Data Engineer or similar role, working with large-scale data processing and storage systems. - Proficiency in SQL and database management systems such as MySQL, PostgreSQL, or Oracle. - Experience with building complex jobs for SCD type mappings using ETL tools like PySpark. - Strong problem-solving and analytical skills, with the ability to handle complex data challenges. - Excellent communication and collaboration skills to work effectively in a team environment. - Experience in data modeling, data warehousing, and ETL principles. - Familiarity with cloud platforms like AWS, Azure, or GCP, and their data services (e.g., S3, Redshift, BigQuery). - Knowledge of containerization and orchestration technologies such as Docker and Kubernetes. - Certification in relevant technologies or data engineering disciplines. You should also be flexible to work in rotational working hours as per business requirements. If you are passionate about data and analytics technologies and eager to work in a collaborative environment where your skills and expertise will be valued, this role is perfect for you. Join us at Baker Hughes and be a part of a team that prioritizes innovation and values the contributions of its employees. As a Staff Business Data Engineer at our Valves team, you will play a crucial role in shaping the future of energy technology using data. You will work at the core of digital transformation, collaborating with teams to solve technical challenges and design innovative solutions. Key Responsibilities: - Designing and implementing scalable and robust data pipelines for collecting, processing, and storing data from various sources. - Developing and maintaining data warehouse and ETL processes for data integration and transformation. - Optimizing data systems' performance to ensure efficient processing and analysis. - Collaborating with product managers and analysts to understand data requirements and implement solutions for data modeling and analysis. - Identifying and resolving data quality issues to ensure accuracy, consistency, and completeness. - Implementing and maintaining data governance and security measures for sensitive data protection. - Monitoring and troubleshooting data infrastructure, performing root cause analysis, and implementing necessary fixes. - Ensuring the use of state-of-the-art methodologies for productive and effective job execution, including researching new technologies in data acquisition and analysis. Qualifications Required: - Bachelors or higher degree in Computer Science, Information Systems, or a related field. - 6-10 years of experience as a Data Engineer or similar role, working with large-scale data processing and storage systems. - Proficiency in SQL and database management systems such as MySQL, PostgreSQL, or Oracle. - Experience with building complex jobs for SCD type mappings using ETL tools like PySpark. - Strong problem-solving and analytical skills, with the ability to handle complex data challenges. - Excellent communication and collaboration skills to work effectively in a team environment. - Experience in data modeling, data warehousing, and ETL principles. - Familiarity with cloud platforms like AWS, Azure, or GCP, and their data services (e.g., S3, Redshift, BigQuery). - Knowledge of containerization and orchestration technologies such as Docker and Kubernetes. - Certification in relevant technologies or data engineering disciplines. You should also be flexible to work in rotational working hours as per business requirements. If you are passionate about data and ana