Remote Real-Time Data Engineer

Description:

• Design and develop real-time data pipelines to ingest, process, and analyze streaming data from various sources, ensuring low-latency and high-throughput.
• Implement stream processing applications using technologies such as Apache Kafka, Apache Flink, Apache Spark Streaming, or AWS Kinesis to process and analyze real-time data streams.
• Integrate real-time data streams with existing data systems and applications, ensuring data consistency and coherence across systems.
• Transform and enrich real-time data streams to derive meaningful insights and enable real-time decision-making, using techniques such as complex event processing (CEP) and real-time analytics.
• Implement data quality checks, validation rules, and error handling mechanisms to ensure the accuracy, completeness, and consistency of real-time data.
• Optimize real-time data processing pipelines for speed, scalability, and efficiency, tuning streaming applications and leveraging distributed computing technologies.
• Monitor real-time data infrastructure and systems for performance, reliability, and availability, proactively identifying and addressing issues to minimize downtime and ensure data integrity.
• Document real-time data architecture, processes, and best practices, and collaborate with cross-functional teams to ensure alignment and transparency.

Requirements:

• Bachelor's degree or higher in Computer Science, Engineering, or related field.
• Strong background in real-time data engineering, with hands-on experience in designing, building, and optimizing real-time data solutions.
• Proficiency in programming languages such as Python, Java, or Scala, and experience with stream processing frameworks such as Apache Kafka, Apache Flink, or Apache Spark Streaming.
• Experience with cloud platforms such as AWS, Google Cloud Platform, or Microsoft Azure, and familiarity with cloud services for real-time data processing (e.g., AWS Kinesis, Google Cloud Dataflow, Azure Stream Analytics).
• Knowledge of distributed computing technologies and concepts, including message brokers, distributed databases, and microservices architecture.
• Strong problem-solving abilities and analytical thinking, with a keen attention to detail and a passion for tackling complex technical challenges.
• 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 Real-Time Data Engineers typically ranges from $140,000 to $210,000 per year, depending on experience and qualifications. Exceptional candidates may be eligible for higher compensation packages.
• 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 team-building activities and social events.
• Opportunities for career growth and advancement within the company.
• Exciting projects with real-world impact in the field of real-time data engineering.
• Chance to work alongside top talent and industry experts in real-time data engineering.