工作描述
7 天前
RevoSurge is a fast-growing technology company redefining digital advertising with innovative, data-driven solutions. Our mission is to empower businesses with a high-performance ad platform that drives exceptional results.
Job Overview
As a Data Platform Engineer, you will design, build, and optimize the data infrastructure that powers our real-time analytics, machine learning models, and business intelligence.
You will work closely with data scientists, engineers, and product teams to ensure our data pipelines are scalable, reliable, and efficient.
Key Responsibilities
• Design, build, and maintain scalable data pipelines for batch and realtime processing.
• Optimize data storage, retrieval, and processing for high performance and cost efficiency.
• Collaborate with Data Scientists & ML Engineers to deploy and manage largescale data workflows.
• Ensure data reliability, quality, and governance across the platform.
• Troubleshoot and resolve issues in distributed data systems (e.g., Spark, Flink, Kafka).
• Improve monitoring, alerting, and observability for data infrastructure.
• Evaluate and integrate new big data technologies to enhance the platform.
Qualifications
Must-Have:
• 5+ years of experience in data engineering, infrastructure, or platform development.
• Strong expertise in distributed systems (e.g., Hadoop, Spark, Flink, Kafka).
• Proficiency in SQL, Python, Java, or Scala.
• Experience with cloud data platforms (AWS, GCP, or Azure).
• Knowledge of data warehousing (e.g., Snowflake, BigQuery, Redshift).
• Familiarity with workflow orchestration (Airflow, Dagster, Prefect).
Good-to-Have:
• Experience with real-time streaming (Kafka, Flink, Beam).
• Knowledge of Kubernetes and infrastructureascode (Terraform, Helm).
• Contributions to opensource data projects.
• Background in ad tech, gaming, or highscale data environments.
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Job Overview
As a Data Platform Engineer, you will design, build, and optimize the data infrastructure that powers our real-time analytics, machine learning models, and business intelligence.
You will work closely with data scientists, engineers, and product teams to ensure our data pipelines are scalable, reliable, and efficient.
Key Responsibilities
• Design, build, and maintain scalable data pipelines for batch and realtime processing.
• Optimize data storage, retrieval, and processing for high performance and cost efficiency.
• Collaborate with Data Scientists & ML Engineers to deploy and manage largescale data workflows.
• Ensure data reliability, quality, and governance across the platform.
• Troubleshoot and resolve issues in distributed data systems (e.g., Spark, Flink, Kafka).
• Improve monitoring, alerting, and observability for data infrastructure.
• Evaluate and integrate new big data technologies to enhance the platform.
Qualifications
Must-Have:
• 5+ years of experience in data engineering, infrastructure, or platform development.
• Strong expertise in distributed systems (e.g., Hadoop, Spark, Flink, Kafka).
• Proficiency in SQL, Python, Java, or Scala.
• Experience with cloud data platforms (AWS, GCP, or Azure).
• Knowledge of data warehousing (e.g., Snowflake, BigQuery, Redshift).
• Familiarity with workflow orchestration (Airflow, Dagster, Prefect).
Good-to-Have:
• Experience with real-time streaming (Kafka, Flink, Beam).
• Knowledge of Kubernetes and infrastructureascode (Terraform, Helm).
• Contributions to opensource data projects.
• Background in ad tech, gaming, or highscale data environments.
Show more Show less
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