We are looking for a Staff Data Engineer to join our dynamic team and play a pivotal role in designing, building, and maintaining our next-generation data platform. You will work closely with data scientists, machine learning engineers, and product managers to deliver robust, scalable, and reliable data solutions that power our AI products.
Responsibilities:
- Architect, design, develop, and maintain data pipelines and infrastructure for batch and real-time data processing.
- Collaborate with data scientists, machine learning engineers, and product managers to understand data requirements and deliver robust data solutions.
- Implement and optimize data models, ensuring data quality, reliability, and scalability.
- Develop tools and frameworks to automate data workflows, monitoring, and alerting.
- Contribute to the continuous improvement of our data platform, advocating for best practices in data engineering and MLOps.
- Mentor junior engineers and foster a culture of technical excellence and innovation.
- Stay abreast of industry trends and emerging technologies, evaluating and recommending their adoption where appropriate.
Prerequisites:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
- 7+ years of experience in data engineering, with a strong focus on building scalable data platforms.
- Expertise in data modeling, ETL/ELT processes, and data warehousing concepts.
- Proficiency in programming languages such as Python or Java/Scala.
- Extensive experience with cloud data platforms (AWS, Azure, GCP) and big data technologies (Spark, Flink, Kafka, Snowflake, Databricks).
- Strong understanding of distributed systems and microservices architecture.
- Familiarity with MLOps principles and tools (MLflow, Kubeflow) is a plus.
- Excellent problem-solving, communication, and collaboration skills.
