Remote Senior Real-Time Data Engineer

Description:

• Design and implement scalable and reliable architecture for real-time data processing and analytics, including data ingestion, processing, and serving layers.
• Develop and maintain real-time data streaming pipelines using technologies such as Apache Kafka, Apache Flink, or Apache Spark Streaming, ensuring low-latency and high-throughput data processing.
• Design event-driven systems to enable real-time processing of data events and triggers, supporting use cases such as real-time monitoring, anomaly detection, and alerting.
• Integrate real-time data streams from diverse sources and systems into the real-time data infrastructure, ensuring data consistency, integrity, and quality.
• Develop real-time analytics systems and dashboards to enable real-time insights and decision-making, leveraging technologies such as Apache Druid, Elasticsearch, or Grafana.
• Implement data governance policies and procedures to ensure data quality, security, and compliance with regulatory requirements in real-time data environments.
• Optimize real-time data pipelines and processing workflows for performance, scalability, and efficiency, leveraging distributed computing and streaming processing techniques.
• Implement monitoring and alerting solutions to track the performance and health of real-time data infrastructure and pipelines, proactively identifying and resolving issues.
• Document real-time data architecture, pipelines, and best practices, providing clear and comprehensive documentation to facilitate understanding and collaboration among team members.
• Collaborate with cross-functional teams, including data scientists, software engineers, and business analysts, to understand requirements and deliver real-time data solutions that meet business needs.
• Mentor junior engineers, sharing expertise and best practices in real-time data engineering, and facilitate knowledge sharing sessions within the team.

Requirements:

• Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field.
• 5+ years of experience in data engineering, with a focus on real-time data technologies.
• Proficiency in real-time data streaming technologies such as Apache Kafka, Apache Flink, or Apache Spark Streaming.
• Strong programming skills in languages such as Python, Java, or Scala, with experience in distributed computing frameworks.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, and services like AWS Kinesis, Azure Stream Analytics, or Google Cloud Dataflow.
• Strong understanding of event-driven architecture and stream processing concepts, with experience building event-driven systems.
• Strong problem-solving skills and analytical thinking, with the ability to design and troubleshoot complex real-time data solutions.
• Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.

Benefits:

• Competitive salary: The industry standard salary for Senior Real-Time Data Engineers typically ranges from $170,000 to $230,000 per year, depending on experience and qualifications.
• Comprehensive health, dental, and vision insurance plans.
• Flexible work hours and remote work options.
• Generous vacation and paid time off.
• Professional development opportunities, including access to training programs, conferences, and workshops.
• State-of-the-art technology environment with access to cutting-edge tools and resources.
• Vibrant and inclusive company culture with opportunities for growth and advancement.
• Exciting projects with real-world impact at the forefront of data-driven innovation.