Senior Data Engineer, PE
Indexed description
What You’ll Be Doing
- Collaborate with multi-functional teams, including full stack engineers, data scientists, data engineers, and DevOps, to craft, implement robust reliable data pipelines, infrastructure and workflows.
- develop and support data models, schemas, and database structures that provide blazing-fast analytics performance. Constantly optimize data workflows to ensure flawless real-time and batch data processing.
- Implement data quality checks and monitoring mechanisms to ensure data integrity and accuracy at every stage. detect and resolve bottlenecks swiftly to maintain a highly available and reliable data ecosystem.
- Control, monitor and optimize worldwide production servers.
- Build and maintain scalable data pipelines, ensuring efficient data storage, retrieval, and transformation.
- Stay ahead of the curve in data engineering technologies and trends. Introduce new tools, techniques, and standard methodologies to improve our data infrastructure, empowering data scientists and analysts alike.
- Feed a culture of learning and knowledge-sharing within the team. Guide and mentor junior data engineers, applying your expertise to uplift the entire department.
- Bachelor’s or master’s degree in computer science, Engineering, or a related field.
- 5+ years of relevant experience.
- Demonstrated track record as a hands-on Data Engineer, driving the successful delivery of sophisticated data projects. Your experience speaks volumes.
- Experience with cloud-based data platforms like AWS, Azure, or GCP. You harness the power of the cloud to unlock data's full potential.
- Strong programming skills in languages such as Python or Scala, with experience in building scalable and efficient systems.
- Experience with containerization technologies like Docker and orchestration tools like Kubernetes.
- Solid knowledge in Linux environment.
- Attention to detail is unwavering. You take pride in delivering data of the highest quality, turning it into insights that power critical business decisions.
- Experience working and data engineering frameworks such as Kafka, Cloudera, Spark, Airflow or Hadoop.
- Growing in a multifaceted environment, able to balance multiple priorities admirably without compromising on quality or precision.
, , JR2021331
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